google research paper publication

Stand on the shoulders of giants

Google Scholar provides a simple way to broadly search for scholarly literature. From one place, you can search across many disciplines and sources: articles, theses, books, abstracts and court opinions, from academic publishers, professional societies, online repositories, universities and other web sites. Google Scholar helps you find relevant work across the world of scholarly research.

How are documents ranked?

Google Scholar aims to rank documents the way researchers do, weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature.

Features of Google Scholar

• Search all scholarly literature from one convenient place
• Explore related works, citations, authors, and publications
• Locate the complete document through your library or on the web
• Keep up with recent developments in any area of research
• Check who's citing your publications, create a public author profile

Disclaimer: Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

• Privacy & Terms

Reference management. Clean and simple.

Google Scholar: the ultimate guide

What is Google Scholar?

Why is google scholar better than google for finding research papers, the google scholar search results page, the first two lines: core bibliographic information, quick full text-access options, "cited by" count and other useful links, tips for searching google scholar, 1. google scholar searches are not case sensitive, 2. use keywords instead of full sentences, 3. use quotes to search for an exact match, 3. add the year to the search phrase to get articles published in a particular year, 4. use the side bar controls to adjust your search result, 5. use boolean operator to better control your searches, google scholar advanced search interface, customizing search preferences and options, using the "my library" feature in google scholar, the scope and limitations of google scholar, alternatives to google scholar, country-specific google scholar sites, frequently asked questions about google scholar, related articles.

Google Scholar (GS) is a free academic search engine that can be thought of as the academic version of Google. Rather than searching all of the indexed information on the web, it searches repositories of:

• universities
• scholarly websites

This is generally a smaller subset of the pool that Google searches. It's all done automatically, but most of the search results tend to be reliable scholarly sources.

However, Google is typically less careful about what it includes in search results than more curated, subscription-based academic databases like Scopus and Web of Science . As a result, it is important to take some time to assess the credibility of the resources linked through Google Scholar.

➡️ Take a look at our guide on the best academic databases .

One advantage of using Google Scholar is that the interface is comforting and familiar to anyone who uses Google. This lowers the learning curve of finding scholarly information .

There are a number of useful differences from a regular Google search. Google Scholar allows you to:

• copy a formatted citation in different styles including MLA and APA
• export bibliographic data (BibTeX, RIS) to use with reference management software
• explore other works have cited the listed work
• easily find full text versions of the article

Although it is free to search in Google Scholar, most of the content is not freely available. Google does its best to find copies of restricted articles in public repositories. If you are at an academic or research institution, you can also set up a library connection that allows you to see items that are available through your institution.

The Google Scholar results page differs from the Google results page in a few key ways. The search result page is, however, different and it is worth being familiar with the different pieces of information that are shown. Let's have a look at the results for the search term "machine learning.”

• The first line of each result provides the title of the document (e.g. of an article, book, chapter, or report).
• The second line provides the bibliographic information about the document, in order: the author(s), the journal or book it appears in, the year of publication, and the publisher.

Clicking on the title link will bring you to the publisher’s page where you may be able to access more information about the document. This includes the abstract and options to download the PDF.

To the far right of the entry are more direct options for obtaining the full text of the document. In this example, Google has also located a publicly available PDF of the document hosted at umich.edu . Note, that it's not guaranteed that it is the version of the article that was finally published in the journal.

Below the text snippet/abstract you can find a number of useful links.

• Cited by : the cited by link will show other articles that have cited this resource. That is a super useful feature that can help you in many ways. First, it is a good way to track the more recent research that has referenced this article, and second the fact that other researches cited this document lends greater credibility to it. But be aware that there is a lag in publication type. Therefore, an article published in 2017 will not have an extensive number of cited by results. It takes a minimum of 6 months for most articles to get published, so even if an article was using the source, the more recent article has not been published yet.
• Versions : this link will display other versions of the article or other databases where the article may be found, some of which may offer free access to the article.
• Quotation mark icon : this will display a popup with commonly used citation formats such as MLA, APA, Chicago, Harvard, and Vancouver that may be copied and pasted. Note, however, that the Google Scholar citation data is sometimes incomplete and so it is often a good idea to check this data at the source. The "cite" popup also includes links for exporting the citation data as BibTeX or RIS files that any major reference manager can import.

Pro tip: Use a reference manager like Paperpile to keep track of all your sources. Paperpile integrates with Google Scholar and many popular academic research engines and databases, so you can save references and PDFs directly to your library using the Paperpile buttons and later cite them in thousands of citation styles:

Although Google Scholar limits each search to a maximum of 1,000 results , it's still too much to explore, and you need an effective way of locating the relevant articles. Here’s a list of pro tips that will help you save time and search more effectively.

You don’t need to worry about case sensitivity when you’re using Google scholar. In other words, a search for "Machine Learning" will produce the same results as a search for "machine learning.”

Let's say your research topic is about self driving cars. For a regular Google search we might enter something like " what is the current state of the technology used for self driving cars ". In Google Scholar, you will see less than ideal results for this query .

The trick is to build a list of keywords and perform searches for them like self-driving cars, autonomous vehicles, or driverless cars. Google Scholar will assist you on that: if you start typing in the search field you will see related queries suggested by Scholar!

If you put your search phrase into quotes you can search for exact matches of that phrase in the title and the body text of the document. Without quotes, Google Scholar will treat each word separately.

This means that if you search national parks , the words will not necessarily appear together. Grouped words and exact phrases should be enclosed in quotation marks.

A search using “self-driving cars 2015,” for example, will return articles or books published in 2015.

Using the options in the left hand panel you can further restrict the search results by limiting the years covered by the search, the inclusion or exclude of patents, and you can sort the results by relevance or by date.

Searches are not case sensitive, however, there are a number of Boolean operators you can use to control the search and these must be capitalized.

• AND requires both of the words or phrases on either side to be somewhere in the record.
• NOT can be placed in front of a word or phrases to exclude results which include them.
• OR will give equal weight to results which match just one of the words or phrases on either side.

➡️ Read more about how to efficiently search online databases for academic research .

In case you got overwhelmed by the above options, here’s some illustrative examples:

Tip: Use the advanced search features in Google Scholar to narrow down your search results.

You can gain even more fine-grained control over your search by using the advanced search feature. This feature is available by clicking on the hamburger menu in the upper left and selecting the "Advanced search" menu item.

Adjusting the Google Scholar settings is not necessary for getting good results, but offers some additional customization, including the ability to enable the above-mentioned library integrations.

The settings menu is found in the hamburger menu located in the top left of the Google Scholar page. The settings are divided into five sections:

• Collections to search: by default Google scholar searches articles and includes patents, but this default can be changed if you are not interested in patents or if you wish to search case law instead.
• Bibliographic manager: you can export relevant citation data via the “Bibliography manager” subsection.
• Languages: if you wish for results to return only articles written in a specific subset of languages, you can define that here.
• Library links: as noted, Google Scholar allows you to get the Full Text of articles through your institution’s subscriptions, where available. Search for, and add, your institution here to have the relevant link included in your search results.
• Button: the Scholar Button is a Chrome extension which adds a dropdown search box to your toolbar. This allows you to search Google Scholar from any website. Moreover, if you have any text selected on the page and then click the button it will display results from a search on those words when clicked.

When signed in, Google Scholar adds some simple tools for keeping track of and organizing the articles you find. These can be useful if you are not using a full academic reference manager.

All the search results include a “save” button at the end of the bottom row of links, clicking this will add it to your "My Library".

To help you provide some structure, you can create and apply labels to the items in your library. Appended labels will appear at the end of the article titles. For example, the following article has been assigned a “RNA” label:

Within your Google Scholar library, you can also edit the metadata associated with titles. This will often be necessary as Google Scholar citation data is often faulty.

There is no official statement about how big the Scholar search index is, but unofficial estimates are in the range of about 160 million , and it is supposed to continue to grow by several million each year.

Yet, Google Scholar does not return all resources that you may get in search at you local library catalog. For example, a library database could return podcasts, videos, articles, statistics, or special collections. For now, Google Scholar has only the following publication types:

• Journal articles : articles published in journals. It's a mixture of articles from peer reviewed journals, predatory journals and pre-print archives.
• Books : links to the Google limited version of the text, when possible.
• Book chapters : chapters within a book, sometimes they are also electronically available.
• Book reviews : reviews of books, but it is not always apparent that it is a review from the search result.
• Conference proceedings : papers written as part of a conference, typically used as part of presentation at the conference.
• Court opinions .
• Patents : Google Scholar only searches patents if the option is selected in the search settings described above.

The information in Google Scholar is not cataloged by professionals. The quality of the metadata will depend heavily on the source that Google Scholar is pulling the information from. This is a much different process to how information is collected and indexed in scholarly databases such as Scopus or Web of Science .

➡️ Visit our list of the best academic databases .

Google Scholar is by far the most frequently used academic search engine , but it is not the only one. Other academic search engines include:

• Science.gov
• Semantic Scholar
• scholar.google.fr : Sur les épaules d'un géant
• scholar.google.es (Google Académico): A hombros de gigantes
• scholar.google.pt (Google Académico): Sobre os ombros de gigantes
• scholar.google.de : Auf den Schultern von Riesen

➡️ Once you’ve found some research, it’s time to read it. Take a look at our guide on how to read a scientific paper .

No. Google Scholar is a bibliographic search engine rather than a bibliographic database. In order to qualify as a database Google Scholar would need to have stable identifiers for its records.

No. Google Scholar is an academic search engine, but the records found in Google Scholar are scholarly sources.

No. Google Scholar collects research papers from all over the web, including grey literature and non-peer reviewed papers and reports.

Google Scholar does not provide any full text content itself, but links to the full text article on the publisher page, which can either be open access or paywalled content. Google Scholar tries to provide links to free versions, when possible.

The easiest way to access Google scholar is by using The Google Scholar Button. This is a browser extension that allows you easily access Google Scholar from any web page. You can install it from the Chrome Webstore .

18 Google Scholar tips all students should know

Dec 13, 2022

[[read-time]] min read

Think of this guide as your personal research assistant.

“It’s hard to pick your favorite kid,” Anurag Acharya says when I ask him to talk about a favorite Google Scholar feature he’s worked on. “I work on product, engineering, operations, partnerships,” he says. He’s been doing it for 18 years, which as of this month, happens to be how long Google Scholar has been around.

Google Scholar is also one of Google’s longest-running services. The comprehensive database of research papers, legal cases and other scholarly publications was the fourth Search service Google launched, Anurag says. In honor of this very important tool’s 18th anniversary, I asked Anurag to share 18 things you can do in Google Scholar that you might have missed.

1. Copy article citations in the style of your choice.

With a simple click of the cite button (which sits below an article entry), Google Scholar will give you a ready-to-use citation for the article in five styles, including APA, MLA and Chicago. You can select and copy the one you prefer.

2. Dig deeper with related searches.

Google Scholar’s related searches can help you pinpoint your research; you’ll see them show up on a page in between article results. Anurag describes it like this: You start with a big topic — like “cancer” — and follow up with a related search like “lung cancer” or “colon cancer” to explore specific kinds of cancer.

Related searches can help you find what you’re looking for.

3. And don’t miss the related articles.

This is another great way to find more papers similar to one you found helpful — you can find this link right below an entry.

4. Read the papers you find.

Scholarly articles have long been available only by subscription. To keep you from having to log in every time you see a paper you’re interested in, Scholar works with libraries and publishers worldwide to integrate their subscriptions directly into its search results. Look for a link marked [PDF] or [HTML]. This also includes preprints and other free-to-read versions of papers.

5. Access Google Scholar tools from anywhere on the web with the Scholar Button browser extension.

The Scholar Button browser extension is sort of like a mini version of Scholar that can move around the web with you. If you’re searching for something, hitting the extension icon will show you studies about that topic, and if you’re reading a study, you can hit that same button to find a version you read, create a citation or to save it to your Scholar library.

Install the Scholar Button Chrome browser extension to access Google Scholar from anywhere on the web.

6. Learn more about authors through Scholar profiles.

There are many times when you’ll want to know more about the researchers behind the ideas you’re looking into. You can do this by clicking on an author’s name when it’s hyperlinked in a search result. You’ll find all of their work as well as co-authors, articles they’re cited in and so on. You can also follow authors from their Scholar profile to get email updates about their work, or about when and where their work is cited.

7. Easily find topic experts.

One last thing about author profiles: If there are topics listed below an author’s name on their profile, you can click on these areas of expertise and you’ll see a page of more authors who are researching and publishing on these topics, too.

8. Search for court opinions with the “Case law” button.

Scholar is the largest free database of U.S. court opinions. When you search for something using Google Scholar, you can select the “Case law” button below the search box to see legal cases your keywords are referenced in. You can read the opinions and a summary of what they established.

9. See how those court opinions have been cited.

If you want to better understand the impact of a particular piece of case law, you can select “How Cited,” which is below an entry, to see how and where the document has been cited. For example, here is the How Cited page for Marbury v. Madison , a landmark U.S. Supreme Court ruling that established that courts can strike down unconstitutional laws or statutes.

10. Understand how a legal opinion depends on another.

When you’re looking at how case laws are cited within Google Scholar, click on “Cited by” and check out the horizontal bars next to the different results. They indicate how relevant the cited opinion is in the court decision it’s cited within. You will see zero, one, two or three bars before each result. Those bars indicate the extent to which the new opinion depends on and refers to the cited case.

In the Cited by page for New York Times Company v. Sullivan, court cases with three bars next to their name heavily reference the original case. One bar indicates less reliance.

11. Sign up for Google Scholar alerts.

Want to stay up to date on a specific topic? Create an alert for a Google Scholar search for your topics and you’ll get email updates similar to Google Search alerts. Another way to keep up with research in your area is to follow new articles by leading researchers. Go to their profiles and click “Follow.” If you’re a junior grad student, you may consider following articles related to your advisor’s research topics, for instance.

12. Save interesting articles to your library.

It’s easy to go down fascinating rabbit hole after rabbit hole in Google Scholar. Don’t lose track of your research and use the save option that pops up under search results so articles will be in your library for later reading.

13. Keep your library organized with labels.

Labels aren’t only for Gmail! You can create labels within your Google Scholar library so you can keep your research organized. Click on “My library,” and then the “Manage labels…” option to create a new label.

14. If you’re a researcher, share your research with all your colleagues.

Many research funding agencies around the world now mandate that funded articles should become publicly free to read within a year of publication — or sooner. Scholar profiles list such articles to help researchers keep track of them and open up access to ones that are still locked down. That means you can immediately see what is currently available from researchers you’re interested in and how many of their papers will soon be publicly free to read.

15. Look through Scholar’s annual top publications and papers.

Every year, Google Scholar releases the top publications based on the most-cited papers. That list (available in 11 languages) will also take you to each publication’s top papers — this takes into account the “h index,” which measures how much impact an article has had. It’s an excellent place to start a research journey as well as get an idea about the ideas and discoveries researchers are currently focused on.

16. Get even more specific with Advanced Search.

Click on the hamburger icon on the upper left-hand corner and select Advanced Search to fine-tune your queries. For example, articles with exact words or a particular phrase in the title or articles from a particular journal and so on.

17. Find extra help on Google Scholar’s help page.

It might sound obvious, but there’s a wealth of useful information to be found here — like how often the database is updated, tips on formatting searches and how you can use your library subscriptions when you’re off-campus (looking at you, college students!). Oh, and you’ll even learn the origin of that quote on Google Scholar’s home page.

18. Keep up with Google Scholar news.

Don’t forget to check out the Google Scholar blog for updates on new features and tips for using this tool even better.

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Google Health research publications

Publishing our work allows us to share ideas and work collaboratively to advance healthcare. This is a comprehensive view of our publications and associated blog posts.

Blog Posts [more at Google Keyword Blog & Google Research Blog ]

by Karen DeSalvo

Google Keyword Blog | 19-Mar-2024

by Ronit Levavi Morad & Preeti Singh

Google Keyword Blog | 8-Mar-2024

Google Keyword Blog | 6-Feb-2024

by Aashima Gupta

Google Keyword Blog | 9-Jan-2024

by Jeff Dean, James Manyika, & Demis Hassabis

Google Research Blog | 22-Dec-2023

by Molly McHugh-Johnson

Google Keyword Blog | 20-Dec-2023

by Ivor Horn

Google Keyword Blog | 2-Nov-2023

by Yossi Mattia Shravya Shetty

Google Keyword Blog | 31-Oct-2023

by Yossi Mattias

Google Keyword Blog | 23-Oct-2023

by Nira Goren

Google Keyword Blog | 18-Oct-2023

by Michaell Howell

Google Keyword Blog | 9-Oct-2023

Google Keyword Blog | 3-Oct-2023

Google Keyword Blog | 18-Jul-2023

Blog Posts [more at Google Keyword Blog & Google AI Blog ]

by Susan Thomas

Google Keyword Blog | 5-Jul-2023

Google Keyword Blog | 13-Jun-2023

Google Keyword Blog | 23-May-2023

Google Keyword Blog | 22-May-2023

by Megan Jones Bell

Google Keyword Blog | 15-May-2023

Google Keyword Blog | 13-Apr-2023

Google Keyword Blog | 14-Mar-2023

by Greg Corrado & Yossi Matias

Google Research Blog | 23-Feb-2023

Google Keyword Blog | 26-Jan-2023

by Katie Malczyk

Google Keyword Blog | 17-Jan-2023

Google Keyword Blog | 5-Jan-2023

by Iz Conroy

Google Keyword Blog | 21-Dec-2022

by Hema Budaraju

Google Keyword Blog | 14-Dec-2022

Google Keyword Blog | 15-Nov-2022

Google Cloud Blog | 14-Nov-2022

by Jeff Dean

Google Keyword Blog | 2-Nov-2022

Google Keyword Blog | 27-Oct-2022

by Riva Sciuto

Google Keyword Blog | 19-Oct-2022

Google Keyword Blog | 12-Sep-2022

by Lauren Winer

Google Keyword Blog | 25-Aug-2022

by Anne Merritt

Google Keyword Blog | 20-Jul-2022

Google Keyword Blog | 17-May-2022

by Megan Jones Bell & Garth Graham

Google Keyword Blog | 10-May-2022

Google Keyword Blog | 24-Mar-2022

by Greg Corrado

Google Research Blog | 24-Mar-2022

by Paul Muret

Google Keyword Blog | 15-Mar-2022

Google Keyword Blog | 8-Mar-2022

Google Research Blog | 11-Jan-2022

Google Keyword Blog | 2-Dec-2021

Google Keyword Blog | 17-Oct-2021

by Alicia Cormie

Google Keyword Blog | 6-May-2021

Google Keyword Blog | 16-Apr-2021

Google Keyword Blog | 23- Feb-2021

Google Research Blog | 12-Jan-2021

by David Feinberg

LinkedIn Blog | 8-Dec-2020

by Dave Greenwood

Google Keyword Blog | 2-Dec-2020

by Anna Lurchenko

Google Design Blog | 29-Jul-2020

by Daniel Gillison, Jr

Google Keyword Blog | 28-May-2020

Google Research Blog | 9-Jan-2020

by Yun Liu & Po-Hsuan Cameron Chen

Google Research Blog | 10-Dec-2019

Google Keyword Blog | 20-Nov-2019

by Ruth Porat

Google Keyword Blog | 21-Oct-2019

by Dominic King

Google Keyword Blog | 18-Sep-2019

Google Research Blog | 15-Jan-2019

Google Keyword Blog | 17-Jun-2019

by Kent Walter

Google Keyword Blog | 13-Dec-2018

Google Research Blog | 12-Jan-2018

by Paula Schnurr & Teri Brister

Google Keyword Blog | 5-Dec-2017

by Mary Giliberti

Google Keyword Blog | 23-Aug-2017

by Katherine Chou

Google Research Blog | 17-May-2017

Google Research Blog | 12-Jan-2017

COVID-19 Blog Posts

Google Keyword Blog | 16-Jun-2022

COVID-19 Blog Posts [more at Google Keyword Blog ]

by Lauren Gallagher

Google Keyword Blog | 11-Feb-2022

Google Keyword Blog | 8-Dec-2021

by Tomer Shekel

Google Keyword Blog | 9-Jun-2021

by the COVID Response team, Google India

Google India Blog | 10-May-2021

Google Keyword Blog | 15-Apr-2021 [Spanish version]

by Stephen Ratcliffe

Google Keyword Blog | 24-Feb-2021

by Sundar Pichai

Google Keyword Blog | 25-Jan-2021

by Steph Hannon

Google Keyword Blog | 11-Dec-2020

by Karen DeSalvo & Kristie Canegallo

Google Keyword Blog | 10-Dec-2020

Google Keyword Blog | 24-Nov-2020 [Spanish version]

Google Keyword Blog

10-Nov-2020

Google Keyword Blog | 27-Oct-2020

Google Keyword Blog | 17-Sept-2020

by Mollie Javerbaum & Meghan Houghton

Google Keyword Blog | 10-Sep-2020

by Evgeniy Gabrilovich

Google Keyword Blog | 2-Sep-2020

by Dave Burke

Google Keyword Blog | 31-Jul-2020

by Apple & Google

Google Keyword Blog | 20-May-2020

by Megan Washam

Google Keyword Blog | 13-May-2020

Google Keyword Blog | 8-May-2020

Google Africa Blog

Google Africa Blog | 23-Apr-2020

Google Keyword Blog | 10-Apr-2020

by Julie Black

Google Keyword Blog | 6-Apr-2020

by Jen Fitzpatrick & Karen DeSalvo

Google Keyword Blog | 3-Apr-2020

by Emily Moxley

Google Keyword Blog | 21-Mar-2020

Google Keyword Blog | 15-Mar-2020

Google Keyword Blog | 6-Mar-2020

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Ann. Intern. Med. 169(12):866-872 (2018).

Curiel-Lewandrowski, C., Novoa, R. A., Berry, E., Celebi, M. E., Codella, N., Giuste, F., Gutman, D., Halpern, A., Leachman, S., Liu, Y., Liu, Y., Reiter, O. & Tschandl, P.

599–628. Springer New York (2019).

Chen, C. P.-H., Liu, Y., & Peng, L.

Nat. Mater. 18, 410–414 (2019). [readcube]

Rajkomar, A., Dean, J., & Kohane I.

N. Engl. J. Med. 380:1347-1358 (2019).

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S. & Dean, J.

Nat. Med. 25, 24–29 (2019). [readcube]

Rough K, Thompson J.

Ophthalmology. 125(8):1136-1138 (2018).

Wachter, R. M., Howell, M. D.

JAMA 320(1):25-26 (2018).

Cross-Specialty Applied AI

by Krishnamurthy (Dj) Dvijotham & Taylan Cemgil

Google Deepmind | 17-Jul-2023

by Shekoofeh Azizi & Laura Culp

Google Research Blog | 26-Apr-2023

by Alex D’Amour & Katherine Heller

Google Research Blog | 18-Oct-2021

by Shekoofeh Azizi

Google Research Blog | 13-Oct-2021

Publications

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Buettner, F., Cardoso, M. J., Cheplygina, V., Chen, J., Christodoulou, E., Cimini, B. A., Farahani, K., Ferrer, L., Galdran, A., van Ginneken, B., Glocker, B., Godau, P., Hashimoto, D. A., Hoffman, M. M., Huisman, M., Isensee, F., Jannin, P., Kahn, C. E., Kainmueller, D., Kainz, B., Karargyris, A., Kleesiek, J., Kofler, F., Kooi, T., Kopp-Schneider, A., Kozubek, M., Kreshuk, A., Kurc, T., Landman, B. A., Litjens, G., Madani, A., Maier-Hein, K., Martel, A. L., Meijering, E., Menze, B., Moons, K. G. M., Müller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rafelski, S. M., Rajpoot, N., Reyes, M., Riegler, M. A., Rieke, N., Saez-Rodriguez, J., Sánchez, C. I., Shetty, S., Summers, R. M., Taha, A. A., Tiulpin, A., Tsaftaris, S. A., Van Calster, B., Varoquaux, G., Yaniv, Z. R., Jäger, P. F. & Maier-Hein, L.

Nat. Methods 21, 182–194 (2024). [readcube]

Brown, A., Tomasev, N., Freyberg, J., Liu, Y., Karthikesalingam, A. & Schrouff, J.

Nat. Commun. 14, 4314 (2023).

Dvijotham, K., Winkens, J., Barsbey, M., Ghaisas, S., Stanforth, R., Pawlowski, N., Strachan, P., Ahmed, Z., Azizi, S., Bachrach, Y., Culp, L., Daswani, M., Freyberg, J., Kelly, C., Kiraly, A., Kohlberger, T., McKinney, S., Mustafa, B., Natarajan, V., Geras, K., Witowski, J., Qin, Z. Z., Creswell, J., Shetty, S., Sieniek, M., Spitz, T., Corrado, G., Kohli, P., Cemgil, T. & Karthikesalingam, A.

Nat. Med. 1–7 (2023).

Azizi, S., Culp, L., Freyberg, J., Mustafa, B., Baur, S., Kornblith, S., Chen, T., Tomasev, N., Mitrović, J., Strachan, P., Mahdavi, S. S., Wulczyn, E., Babenko, B., Walker, M., Loh, A., Chen, P.-H. C., Liu, Y., Bavishi, P., McKinney, S. M., Winkens, J., Roy, A. G., Beaver, Z., Ryan, F., Krogue, J., Etemadi, M., Telang, U., Liu, Y., Peng, L., Corrado, G. S., Webster, D. R., Fleet, D., Hinton, G., Houlsby, N., Karthikesalingam, A., Norouzi, M. & Natarajan, V.

Nature Biomedical Engineering 1–24 (2023). [readcube]

Schrouff, J., Harris, N., Koyejo, O. O., Alabdulmohsin, I., Schnider, E., Opsahl-Ong, K., Brown, A., Roy, S., Mincu, D., Chen, C., Dieng, A., Liu, Y., Natarajan, V., Karthikesalingam, A., Heller, K. A., Chiappa, S. & D’Amour, A.

NeurIPS (2022).

McKinney, S. M.

medRxiv (2022).

Freeman, B., Hammel, N., Phene, S., Huang, A., Ackermann, R., Kanzheleva, O., Hutson, M., Taggart, C., Duong, Q. & Sayres, R.

HCOMP 9, 60–71 (2021).

Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., Natarajan, V. & Norouzi, M.

Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 3478–3488 (2021).

Sadilek, A., Liu, L., Nguyen, D., Kamruzzaman, M., Serghiou, S., Rader, B., Ingerman, A., Mellem, S., Kairouz, P., Nsoesie, E. O., MacFarlane, J., Vullikanti, A., Marathe, M., Eastham, P., Brownstein, J. S., Arcas, B. A. Y., Howell, M. D. & Hernandez, J.

NPJ Digit Med 4, 132 (2021).

Mustafa, B., Loh, A., Freyberg, J., MacWilliams, P., Karthikesalingam, A., Houlsby, N. & Natarajan, V.

arXiv [cs.CV] (2021).

arXiv [eess.IV] (2021).

D’Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., Hormozdiari, F., Houlsby, N., Hou, S., Jerfel, G., Karthikesalingam, A., Lucic, M., Ma, Y., McLean, C., Mincu, D., Mitani, A., Montanari, A., Nado, Z., Natarajan, V., Nielson, C., Osborne, T. F., Raman, R., Ramasamy, K., Sayres, R., Schrouff, J., Seneviratne, M., Sequeira, S., Suresh, H., Veitch, V., Vladymyrov, M., Wang, X., Webster, K., Yadlowsky, S., Yun, T., Zhai, X. & Sculley, D.

arXiv [cs.LG] (2020).

Winkens, J., Bunel, R., Roy, A. G., Stanforth, R., Natarajan, V., Ledsam, J. R., MacWilliams, P., Kohli, P., Karthikesalingam, A., Kohl, S., Cemgil, T., Ali Eslami, S. M. & Ronneberger, O.

Hartman, T., Howell, M., Dean, J., Hoory, S., Slyper, R., Laish, I., Gilon, O, Vainstein, D., Corrado, G., Chou, K., Po, M., Williams, J., Ellis, S., Bee, G., Hassidim, A., Amira, R., Beryozkin, G., Szpektor, I., & Matias, Y.

BMC (2020).

Dermatology

by Pooja Rao

Google Research Blog | 19-Mar-2024

by Mike Schaekermann & Ivor Horn

Google Research Blog | 15-Mar-2024

by Dave Steiner & Rory Pilgrim

Google Research Blog | 8-Mar-2024

by Lou Wang

Google Keyword Blog | 14-Jun-2023

Google Keyword Blog | 08-Feb-2022

by Abhijit Guha Roy & Jie Ren

Google Research Blog | 27-Jan-2022

by Miles Hutson & Aaron Loh

TensorFlow Blog | 11-Oct-2021

by Peggy Bui & Yuan Liu

Google Keyword Blog | 18-May-2021

by Ayush Jain & Peggy Bui

Google Keyword Blog | 28-Apr-2021

by Timo Kohlberger & Yuan Liu

Google Research Blog | 19-Feb-2020

by Yuan Liu & Peggy Bui

Google Research Blog | 12-Sep-2019

Schaekermann, M., Spitz, T., Pyles, M., Cole-Lewis, H., Wulczyn, E., Pfohl, S. R., Martin, D., Jr, Jaroensri, R., Keeling, G., Liu, Y., Farquhar, S., Xue, Q., Lester, J., Hughes, C., Strachan, P., Tan, F., Bui, P., Mermel, C. H., Peng, L. H., Matias, Y., Corrado, G. S., Webster, D. R., Virmani, S., Semturs, C., Liu, Y., Horn, I. & Cameron Chen, P.-H.

eClinicalMedicine (2024).

Rikhye, R. V., Hong, G. E., Singh, P., Smith, M. A., Loh, A., Muralidharan, V., Wong, D., Sayres, R., Phung, M., Betancourt, N., Fong, B., Sahasrabudhe, R., Nasim, K., Eschholz, A., Matias, Y., Corrado, G. S., Chou, K., Webster, D. R., Bui, P., Liu, Y., Liu, Y., Ko, J. & Lin, S.

Mayo Clinic Proceedings: Digital Health (2024).

Alabdulmohsin, I.M., Schrouff, J., Koyejo, S.

35. NeurIPS (2022).

Vemulapalli, R., Morningstar, W. R., Mansfield, P. A., Eichner, H., Singhal, K., Afkanpour, A. & Green, B.

arXiv [cs.LG] (2022).

Huang, S. J., Liu, Y., Kanada, K., Corrado, G. S., Webster, D. R., Peng, L., Bui, P. & Liu, Y.

Skin Health and Disease (2021).

Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., Vo, N., Bui, P., Winter, S., MacWilliams, P., Corrado, G. S., Telang, U., Liu, Y., Cemgil, T., Karthikesalingam, A., Lakshminarayanan, B. & Winkens, J.

Med. Image Analysis. 75, 102274 (2021). [ reading link ]

Weng, W.-H., Deaton, J., Natarajan, V., Elsayed, G. F. & Liu, Y.

JAMA Netw Open 4, e217249–e217249 (2021).

Machine Learning for Health NeurIPS Workshop (ML4H), PMLR 136:415-429 (2020).

Singh, N., Lee, K., Coz, D., Angermueller, C., Huang, S., Loh, A. & Liu, Y.

in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 3172–3181 (2020).

Liu, Y., Jain, A., Eng, C., Way, D. H., Lee, K., Bui, P., Kanada, K., de Oliveira Marinho, G., Gallegos, J., Gabriele, S., Gupta, V., Singh, N., Natarajan, V., Hofmann-Wellenhof, R., Corrado, G. S., Peng, L. H., Webster, D. R., Ai, D., Huang, S., Liu, Y., Carter Dunn, R. & Coz, D.

Nat. Med. (2020). [readcube]

Ghorbani, A., Natarajan, V., Coz, D. & Liu, Y.

Machine Learning for Health NeurIPS Workshop (ML4H), PMLR 116:155-170 (2020).

Eng, C., Liu, Y. & Bhatnagar, R.

Br. J. Dermatol. (2019). readcube

by Yossi Matias & Ehud Rivlin

Google Research Blog | 5-Aug-2021

by Robin Suchan

Verily Press | 5-Aug-2021

by Daniel Freedman & Ehud Rivlin

Google Research Blog | 28-Aug-2020

Golany, T., Aides, A., Freedman, D., Rabani, N., Liu, Y., Rivlin, E., Corrado, G. S., Matias, Y., Khoury, W., Kashtan, H. & Reissman, P.

Surg. Endosc. (2022).

Livovsky, D. M., Veikherman, D., Golany, T., Aides, A., Dashinsky, V., Rabani, N., Ben Shimol, D., Blau, Y., Katzir, L., Shimshoni, I., Liu, Y., Segol, O., Goldin, E., Corrado, G., Lachter, J., Matias, Y., Rivlin, E. & Freedman, D.

Gastrointest. Endosc. (2021).

Freedman, D., Blau, Y., Katzir, L., Aides, A., Shimshoni, I., Veikherman, D., Golany, T., Gordon, A., Corrado, G., Matias, Y. & Rivlin, E.

IEEE Trans. Med. Imaging 1–1 (2020).

Epidemiological Forecasting

by Joel Shor & Sercan Arik

by Tomas Pfister

Google Cloud Blog | 15-Nov-2020

by Dario Sava

Google Cloud Blog | 3-Aug-2020

Tsai, T. C., Arik, S., Jacobson, B. H., Yoon, J., Yoder, N., Sava, D., Mitchell, M., Graham, G. & Pfister, T.

NPJ Digit Med 5, 59 (2022).

Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., Gerding, A., Gneiting, T., House, K. H., Huang, Y., Jayawardena, D., Kanji, A. H., Khandelwal, A., Le, K., Mühlemann, A., Niemi, J., Shah, A., Stark, A., Wang, Y., Wattanachit, N., Zorn, M. W., Gu, Y., Jain, S., Bannur, N., Deva, A., Kulkarni, M., Merugu, S., Raval, A., Shingi, S., Tiwari, A., White, J., Abernethy, N. F., Woody, S., Dahan, M., Fox, S., Gaither, K., Lachmann, M., Meyers, L. A., Scott, J. G., Tec, M., Srivastava, A., George, G. E., Cegan, J. C., Dettwiller, I. D., England, W. P., Farthing, M. W., Hunter, R. H., Lafferty, B., Linkov, I., Mayo, M. L., Parno, M. D., Rowland, M. A., Trump, B. D., Zhang-James, Y., Chen, S., Faraone, S. V., Hess, J., Morley, C. P., Salekin, A., Wang, D., Corsetti, S. M., Baer, T. M., Eisenberg, M. C., Falb, K., Huang, Y., Martin, E. T., McCauley, E., Myers, R. L., Schwarz, T., Sheldon, D., Gibson, G. C., Yu, R., Gao, L., Ma, Y., Wu, D., Yan, X., Jin, X., Wang, Y.-X., Chen, Y., Guo, L., Zhao, Y., Gu, Q., Chen, J., Wang, L., Xu, P., Zhang, W., Zou, D., Biegel, H., Lega, J., McConnell, S., Nagraj, V. P., Guertin, S. L., Hulme-Lowe, C., Turner, S. D., Shi, Y., Ban, X., Walraven, R., Hong, Q.-J., Kong, S., van de Walle, A., Turtle, J. A., Ben-Nun, M., Riley, S., Riley, P., Koyluoglu, U., DesRoches, D., Forli, P., Hamory, B., Kyriakides, C., Leis, H., Milliken, J., Moloney, M., Morgan, J., Nirgudkar, N., Ozcan, G., Piwonka, N., Ravi, M., Schrader, C., Shakhnovich, E., Siegel, D., Spatz, R., Stiefeling, C., Wilkinson, B., Wong, A., Cavany, S., España, G., Moore, S., Oidtman, R., Perkins, A., Kraus, D., Kraus, A., Gao, Z., Bian, J., Cao, W., Lavista Ferres, J., Li, C., Liu, T.-Y., Xie, X., Zhang, S., Zheng, S., Vespignani, A., Chinazzi, M., Davis, J. T., Mu, K., Pastore Y Piontti, A., Xiong, X., Zheng, A., Baek, J., Farias, V., Georgescu, A., Levi, R., Sinha, D., Wilde, J., Perakis, G., Bennouna, M. A., Nze-Ndong, D., Singhvi, D., Spantidakis, I., Thayaparan, L., Tsiourvas, A., Sarker, A., Jadbabaie, A., Shah, D., Della Penna, N., Celi, L. A., Sundar, S., Wolfinger, R., Osthus, D., Castro, L., Fairchild, G., Michaud, I., Karlen, D., Kinsey, M., Mullany, L. C., Rainwater-Lovett, K., Shin, L., Tallaksen, K., Wilson, S., Lee, E. C., Dent, J., Grantz, K. H., Hill, A. L., Kaminsky, J., Kaminsky, K., Keegan, L. T., Lauer, S. A., Lemaitre, J. C., Lessler, J., Meredith, H. R., Perez-Saez, J., Shah, S., Smith, C. P., Truelove, S. A., Wills, J., Marshall, M., Gardner, L., Nixon, K., Burant, J. C., Wang, L., Gao, L., Gu, Z., Kim, M., Li, X., Wang, G., Wang, Y., Yu, S., Reiner, R. C., Barber, R., Gakidou, E., Hay, S. I., Lim, S., Murray, C., Pigott, D., Gurung, H. L., Baccam, P., Stage, S. A., Suchoski, B. T., Prakash, B. A., Adhikari, B., Cui, J., Rodríguez, A., Tabassum, A., Xie, J., Keskinocak, P., Asplund, J., Baxter, A., Oruc, B. E., Serban, N., Arik, S. O., Dusenberry, M., Epshteyn, A., Kanal, E., Le, L. T., Li, C.-L., Pfister, T., Sava, D., Sinha, R., Tsai, T., Yoder, N., Yoon, J., Zhang, L., Abbott, S., Bosse, N. I., Funk, S., Hellewell, J., Meakin, S. R., Sherratt, K., Zhou, M., Kalantari, R., Yamana, T. K., Pei, S., Shaman, J., Li, M. L., Bertsimas, D., Skali Lami, O., Soni, S., Tazi Bouardi, H., Ayer, T., Adee, M., Chhatwal, J., Dalgic, O. O., Ladd, M. A., Linas, B. P., Mueller, P., Xiao, J., Wang, Y., Wang, Q., Xie, S., Zeng, D., Green, A., Bien, J., Brooks, L., Hu, A. J., Jahja, M., McDonald, D., Narasimhan, B., Politsch, C., Rajanala, S., Rumack, A., Simon, N., Tibshirani, R. J., Tibshirani, R., Ventura, V., Wasserman, L., O’Dea, E. B., Drake, J. M., Pagano, R., Tran, Q. T., Ho, L. S. T., Huynh, H., Walker, J. W., Slayton, R. B., Johansson, M. A., Biggerstaff, M. & Reich, N. G.

Proc. Natl. Acad. Sci. U. S. A. 119, e2113561119 (2022).

Arık, S. Ö., Shor, J., Sinha, R., Yoon, J., Ledsam, J. R., Le, L. T., Dusenberry, M. W., Yoder, N. C., Popendorf, K., Epshteyn, A., Euphrosine, J., Kanal, E., Jones, I., Li, C.-L., Luan, B., Mckenna, J., Menon, V., Singh, S., Sun, M., Ravi, A. S., Zhang, L., Sava, D., Cunningham, K., Kayama, H., Tsai, T., Yoneoka, D., Nomura, S., Miyata, H. & Pfister, T.

NPJ Digit Med 4, 146 (2021).

Kapoor, A., Ben, X., Liu, L., Perozzi, B., Barnes, M., Blais, M. & O’Banion, S.

Arik, Li, Yoon, Sinha, Epshteyn, Le, Menon, Singh, Zhang, Nikoltchev, Sonthalia, Nakhost, Kanal & Pfister.

Adv. Neural Inf. Process. Syst. 2020.

Eye Diseases

by Michelle Budzyna & Molly McHugh-Johnson

Google Keyword Blog | 27-Sep-2023

by Kasumi Widner

Google Keyword Blog | 30-May-2023

by Angus Turner

Google Australia Blog | 7-Mar-2023

by Emma Beede

Google Keyword Blog | 25-Apr-2020

by Kasumi Widner & Sunny Virmani

Google Keyword Blog | 25-Feb-2019

Verily Blog | 25-Feb-2019

by Rory Sayres & Jonathan Krause

Google Research Blog | 13-Dec-2018

by Mustafa Suleyman

DeepMind Blog | 13-Aug-2018

by Lily Peng

Google Keyword Blog | 29-Nov-2016

by Lily Peng & Varun Gulshan

Google Research Blog | 29-Nov-2016

Bora, A., Tiwari, R., Bavishi, P., Virmani, S., Huang, R., Traynis, I., Corrado, G. S., Peng, L., Webster, D. R., Varadarajan, A. V., Pattanapongpaiboon, W., Chopra, R. & Ruamviboonsuk, P.

Transl. Vis. Sci. Technol. 12, 11 (2023).

Widner, K., Virmani, S., Krause, J., Nayar, J., Tiwari, R., Pedersen, E. R., Jeji, D., Hammel, N., Matias, Y., Corrado, G. S., Liu, Y., Peng, L. & Webster, D. R.

Nat. Med. 1–3 (2023). [readcube]

Srisubat, A., Kittrongsiri, K., Sangroongruangsri, S., Khemvaranan, C., Shreibati, J. B., Ching, J., Hernandez, J., Tiwari, R., Hersch, F., Liu, Y., Hanutsaha, P., Ruamviboonsuk, V., Turongkaravee, S., Raman, R. & Ruamviboonsuk, P.

Ophthalmol Ther (2023).

Chia, M. A., Hersch, F., Sayres, R., Bavishi, P., Tiwari, R., Keane, P. A. & Turner, A. W.

Br. J. Ophthalmol. (2023).

Ruamviboonsuk, P., Tiwari, R., Sayres, R., Nganthavee, V., Hemarat, K., Kongprayoon, A., Raman, R., Levinstein, B., Liu, Y., Schaekermann, M., Lee, R., Virmani, S., Widner, K., Chambers, J., Hersch, F., Peng, L. & Webster, D. R.

The Lancet Digital Health (2022).

Pedersen Elin Rønby, Cuadros Jorge, Khan Mahbuba, Fleischmann Sybille, Wolff Gregory, Hammel Naama, Liu Yun & Leung Geoffrey.

NEJM Catalyst (2021).

Wilson, M., Chopra, R., Wilson, M. Z., Cooper, C., MacWilliams, P., Liu, Y., Wulczyn, E., Florea, D., Hughes, C. O., Karthikesalingam, A., Khalid, H., Vermeirsch, S., Nicholson, L., Keane, P. A., Balaskas, K. & Kelly, C. J.

JAMA Ophthalmol. (2021).

Limwattanayingyong, J., Nganthavee, V., Seresirikachorn, K., Singalavanija, T., Soonthornworasiri, N., Ruamviboonsuk, V., Rao, C., Raman, R., Grzybowski, A., Schaekermann, M., Peng, L. H., Webster, D. R., Semturs, C., Krause, J., Sayres, R., Hersch, F., Tiwari, R., Liu, Y. & Ruamviboonsuk, P.

Journal of Diabetes Research, 1–8 (2020).

Hsu J, Phene S, Mitani A, Luo J, Hammel N, Krause J, Sayres R.

in ACM-CHIL [arXiv] (2020)

Bresnick, G., Cuadros, J. A., Khan, M., Fleischmann, S., Wolff, G., Limon, A., Chang, J., Jiang, L., Cuadros, P. & Pedersen, E. R.

BMJ Open Diabetes Research and Care 8, e001154 (2020).

Beede, E., Baylor, E., Hersch, F., Iurchenko, A., Wilcox, L., Ruamviboonsuk, P. & Vardoulakis, L. M.

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems 1–12. Association for Computing Machinery (2020).

Schaekermann, M., Cai, C. J., Huang, A. E. & Sayres, R.

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems 1–13. Association for Computing Machinery (2020).

Phene, S., Dunn, R. C., Hammel, N., Liu, Y., Krause, J., Kitade, N., Schaekermann, M., Sayres, R., Wu, D. J., Bora, A., Semturs, C., Misra, A., Huang, A. E., Spitze, A., Medeiros, F. A., Maa, A. Y., Gandhi, M., Corrado, G. S., Peng, L. & Webster, D. R.

Ophthalmology 126, 1627–1639 (2019).

Schaekermann, M., Hammel, N., Terry, M., Ali, T. K., Liu, Y., Basham, B., Campana, B., Chen, W., Ji, X., Krause, J., Corrado, G. S., Peng, L., Webster, D. R., Law, E. & Sayres, R.

Transl. Vis. Sci. Technol. 8, 40 (2019).

Gulshan, V., Rajan, R. P., Widner, K., Wu, D., Wubbels, P., Rhodes, T., Whitehouse, K., Coram, M., Corrado, G., Ramasamy, K., Raman, R., Peng, L. & Webster, D. R.

JAMA Ophthalmol. (2019).

Ruamviboonsuk, P., Krause, J., Chotcomwongse, P., Sayres, R., Raman, R., Widner, K., Campana, B. J. L., Phene, S., Hemarat, K., Tadarati, M., Silpa-Archa, S., Limwattanayingyong, J., Rao, C., Kuruvilla, O., Jung, J., Tan, J., Orprayoon, S., Kangwanwongpaisan, C., Sukumalpaiboon, R., Luengchaichawang, C., Fuangkaew, J., Kongsap, P., Chualinpha, L., Saree, S., Kawinpanitan, S., Mitvongsa, K., Lawanasakol, S., Thepchatri, C., Wongpichedchai, L., Corrado, G. S., Peng, L. & Webster, D. R.

npj Digit Med 2, 25 (2019).

Sayres, R., Taly, A., Rahimy, E., Blumer, K., Coz, D., Hammel, N., Krause, J., Narayanaswamy, A., Rastegar, Z., Wu, D., Xu, S., Barb, S., Joseph, A., Shumski, M., Smith, J., Sood, A. B., Corrado, G. S., Peng, L. & Webster, D. R.

Ophthalmology 126, 552–564 (2019).

Fauw, J., Ledsam, J.R., Romera-Paredes, B., Nikolov, S., Tomasev, N., Blackwell, S., Askham, H., Glorot, X., O’Donoghue, B., Visentin, D., van den Driessche, G., Lakshminarayanan, B., Meyer, C., Mackinder, F., Bouton, S., Ayoub, K., Chopra, R., King, D., Karthikesalingam, A., Hughes, C.O., Raine, R., Hughes, J., Sim, D. A., Egan, C., Tufail, A., Montgomery, H., Hassabis, D., Rees, G., Back, T., Khaw, P.T., Suleyman, M., Cornebise, J., Keane, P.A., & Ronneberger, O.

Nat. Med. 24, 1342–1350 (2018). [readcube]

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by Boris Babenko & Akib Uddin

Google Research Blog | 24-Mar-2023

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by Terry Spitz & Jim Winkens

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Open Health Stack

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by Yossi Mattia & Shravya Shetty

by Richa Tiwari

Open Health Stack Blog | 10-Oct-2023.

Open Health Stack Blog | 2-Sep-2023.

by Abirami Sukumaran & Omar Ismail

Google Cloud Blog | 17-Aug-2023.

by Fred Hersch

Google Keyword Blog | 14-Mar-2023.

by Katherine Chou & Sudhi Herle

Android Developers Blog | 24-Mar-2022

by Fred Hersch & Jing Tang

Mehl, G. L., Seneviratne, M. G., Berg, M. L., Bidani, S., Distler, R. L., Gorgens, M., Kallander, K. E., Labrique, A. B., Landry, M. S., Leitner, C., Lubell-Doughtie, P. B., Marcelo, A. D., Matias, Y., Nelson, J., Nguyen, V., Nsengimana, J. P., Orton, M., Otzoy Garcia, D. R., Oyaole, D. R., Ratanaprayul, N., Roth, S., Schaefer, M. P., Settle, D., Tang, J., Tien-Wahser, B., Wanyee, S. & Hersch, F.

Oxf Open Digit Health, (2023).

Digital Public Goods Alliance - Promoting digital public goods to create a more equitable world (2023). 14-Dec-2023.

Google Open Source Blog | 17-May-2023

by Justin Krogue, Yun Liu, Po-Hsuan Cameron Chen & Ellery A

Nature Portfolio Health Community Blog | 10-May-2023

by Ellery Wulczyn and Yun Liu

Google Research Blog | 14-Mar-2023

Google Cloud Blog | 12-Dec-2022

Verily Blog | 16-Mar-2022

by Po-Hsuan Cameron Chen & Maggie Demkin

Google Research Blog | 11-Feb-2022

by Po-Hsuan Cameron Chen & Yun Liu

Google Keyword Blog | 23-Sept-2021

by People + AI Research

People + AI Research Blog | 14-May-2021

by Dave Steiner, Yun Liu, Craig Mermel, Kurt Zatloukal, Heimo Muller, Markus Plass

npj Digital Medicine Blog | 19-Apr-2021

Google Cloud Blog | 2-Sep-2020

by Kunal Nagpal & Craig Mermel

Google Keyword Blog | 23-Jul-2020

by Narayan Hedge & Carrie Cai

Google Research Blog | 19-July-2019

by Martin Stumpe & Craig Mermel

Google Research Blog | 16-Nov-2018

Google Research Blog | 12-Oct-2018

Google Research Blog | 16-Apr-2018

by Martin Stumpe & Lily Peng

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by Kristina Gligoric

Nature Portfolio Health Community Blog | 22-Nov-2023

Google Keyword | 10-Oct-2023

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Google Africa Blog | 9-May-2023

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Google Keyword Blog | 29-Mar-2023

by Adam Sadilek & Xerxes Dotiwalla

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How to Write and Publish a Research Paper for a Peer-Reviewed Journal

• Open access
• Published: 30 April 2020
• Volume 36 , pages 909–913, ( 2021 )

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• Clara Busse   ORCID: orcid.org/0000-0002-0178-1000 1 &
• Ella August   ORCID: orcid.org/0000-0001-5151-1036 1 , 2  

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Communicating research findings is an essential step in the research process. Often, peer-reviewed journals are the forum for such communication, yet many researchers are never taught how to write a publishable scientific paper. In this article, we explain the basic structure of a scientific paper and describe the information that should be included in each section. We also identify common pitfalls for each section and recommend strategies to avoid them. Further, we give advice about target journal selection and authorship. In the online resource 1 , we provide an example of a high-quality scientific paper, with annotations identifying the elements we describe in this article.

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Introduction

Writing a scientific paper is an important component of the research process, yet researchers often receive little formal training in scientific writing. This is especially true in low-resource settings. In this article, we explain why choosing a target journal is important, give advice about authorship, provide a basic structure for writing each section of a scientific paper, and describe common pitfalls and recommendations for each section. In the online resource 1 , we also include an annotated journal article that identifies the key elements and writing approaches that we detail here. Before you begin your research, make sure you have ethical clearance from all relevant ethical review boards.

Select a Target Journal Early in the Writing Process

We recommend that you select a “target journal” early in the writing process; a “target journal” is the journal to which you plan to submit your paper. Each journal has a set of core readers and you should tailor your writing to this readership. For example, if you plan to submit a manuscript about vaping during pregnancy to a pregnancy-focused journal, you will need to explain what vaping is because readers of this journal may not have a background in this topic. However, if you were to submit that same article to a tobacco journal, you would not need to provide as much background information about vaping.

Information about a journal’s core readership can be found on its website, usually in a section called “About this journal” or something similar. For example, the Journal of Cancer Education presents such information on the “Aims and Scope” page of its website, which can be found here: https://www.springer.com/journal/13187/aims-and-scope .

Peer reviewer guidelines from your target journal are an additional resource that can help you tailor your writing to the journal and provide additional advice about crafting an effective article [ 1 ]. These are not always available, but it is worth a quick web search to find out.

Identify Author Roles Early in the Process

Early in the writing process, identify authors, determine the order of authors, and discuss the responsibilities of each author. Standard author responsibilities have been identified by The International Committee of Medical Journal Editors (ICMJE) [ 2 ]. To set clear expectations about each team member’s responsibilities and prevent errors in communication, we also suggest outlining more detailed roles, such as who will draft each section of the manuscript, write the abstract, submit the paper electronically, serve as corresponding author, and write the cover letter. It is best to formalize this agreement in writing after discussing it, circulating the document to the author team for approval. We suggest creating a title page on which all authors are listed in the agreed-upon order. It may be necessary to adjust authorship roles and order during the development of the paper. If a new author order is agreed upon, be sure to update the title page in the manuscript draft.

In the case where multiple papers will result from a single study, authors should discuss who will author each paper. Additionally, authors should agree on a deadline for each paper and the lead author should take responsibility for producing an initial draft by this deadline.

Structure of the Introduction Section

The introduction section should be approximately three to five paragraphs in length. Look at examples from your target journal to decide the appropriate length. This section should include the elements shown in Fig.  1 . Begin with a general context, narrowing to the specific focus of the paper. Include five main elements: why your research is important, what is already known about the topic, the “gap” or what is not yet known about the topic, why it is important to learn the new information that your research adds, and the specific research aim(s) that your paper addresses. Your research aim should address the gap you identified. Be sure to add enough background information to enable readers to understand your study. Table 1 provides common introduction section pitfalls and recommendations for addressing them.

The main elements of the introduction section of an original research article. Often, the elements overlap

Methods Section

The purpose of the methods section is twofold: to explain how the study was done in enough detail to enable its replication and to provide enough contextual detail to enable readers to understand and interpret the results. In general, the essential elements of a methods section are the following: a description of the setting and participants, the study design and timing, the recruitment and sampling, the data collection process, the dataset, the dependent and independent variables, the covariates, the analytic approach for each research objective, and the ethical approval. The hallmark of an exemplary methods section is the justification of why each method was used. Table 2 provides common methods section pitfalls and recommendations for addressing them.

Results Section

The focus of the results section should be associations, or lack thereof, rather than statistical tests. Two considerations should guide your writing here. First, the results should present answers to each part of the research aim. Second, return to the methods section to ensure that the analysis and variables for each result have been explained.

Begin the results section by describing the number of participants in the final sample and details such as the number who were approached to participate, the proportion who were eligible and who enrolled, and the number of participants who dropped out. The next part of the results should describe the participant characteristics. After that, you may organize your results by the aim or by putting the most exciting results first. Do not forget to report your non-significant associations. These are still findings.

Tables and figures capture the reader’s attention and efficiently communicate your main findings [ 3 ]. Each table and figure should have a clear message and should complement, rather than repeat, the text. Tables and figures should communicate all salient details necessary for a reader to understand the findings without consulting the text. Include information on comparisons and tests, as well as information about the sample and timing of the study in the title, legend, or in a footnote. Note that figures are often more visually interesting than tables, so if it is feasible to make a figure, make a figure. To avoid confusing the reader, either avoid abbreviations in tables and figures, or define them in a footnote. Note that there should not be citations in the results section and you should not interpret results here. Table 3 provides common results section pitfalls and recommendations for addressing them.

Discussion Section

Opposite the introduction section, the discussion should take the form of a right-side-up triangle beginning with interpretation of your results and moving to general implications (Fig.  2 ). This section typically begins with a restatement of the main findings, which can usually be accomplished with a few carefully-crafted sentences.

Major elements of the discussion section of an original research article. Often, the elements overlap

Next, interpret the meaning or explain the significance of your results, lifting the reader’s gaze from the study’s specific findings to more general applications. Then, compare these study findings with other research. Are these findings in agreement or disagreement with those from other studies? Does this study impart additional nuance to well-accepted theories? Situate your findings within the broader context of scientific literature, then explain the pathways or mechanisms that might give rise to, or explain, the results.

Journals vary in their approach to strengths and limitations sections: some are embedded paragraphs within the discussion section, while some mandate separate section headings. Keep in mind that every study has strengths and limitations. Candidly reporting yours helps readers to correctly interpret your research findings.

The next element of the discussion is a summary of the potential impacts and applications of the research. Should these results be used to optimally design an intervention? Does the work have implications for clinical protocols or public policy? These considerations will help the reader to further grasp the possible impacts of the presented work.

Finally, the discussion should conclude with specific suggestions for future work. Here, you have an opportunity to illuminate specific gaps in the literature that compel further study. Avoid the phrase “future research is necessary” because the recommendation is too general to be helpful to readers. Instead, provide substantive and specific recommendations for future studies. Table 4 provides common discussion section pitfalls and recommendations for addressing them.

Follow the Journal’s Author Guidelines

After you select a target journal, identify the journal’s author guidelines to guide the formatting of your manuscript and references. Author guidelines will often (but not always) include instructions for titles, cover letters, and other components of a manuscript submission. Read the guidelines carefully. If you do not follow the guidelines, your article will be sent back to you.

Finally, do not submit your paper to more than one journal at a time. Even if this is not explicitly stated in the author guidelines of your target journal, it is considered inappropriate and unprofessional.

Your title should invite readers to continue reading beyond the first page [ 4 , 5 ]. It should be informative and interesting. Consider describing the independent and dependent variables, the population and setting, the study design, the timing, and even the main result in your title. Because the focus of the paper can change as you write and revise, we recommend you wait until you have finished writing your paper before composing the title.

Be sure that the title is useful for potential readers searching for your topic. The keywords you select should complement those in your title to maximize the likelihood that a researcher will find your paper through a database search. Avoid using abbreviations in your title unless they are very well known, such as SNP, because it is more likely that someone will use a complete word rather than an abbreviation as a search term to help readers find your paper.

After you have written a complete draft, use the checklist (Fig. 3 ) below to guide your revisions and editing. Additional resources are available on writing the abstract and citing references [ 5 ]. When you feel that your work is ready, ask a trusted colleague or two to read the work and provide informal feedback. The box below provides a checklist that summarizes the key points offered in this article.

Checklist for manuscript quality

Data Availability

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Acknowledgments

Ella August is grateful to the Sustainable Sciences Institute for mentoring her in training researchers on writing and publishing their research.

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Busse, C., August, E. How to Write and Publish a Research Paper for a Peer-Reviewed Journal. J Canc Educ 36 , 909–913 (2021). https://doi.org/10.1007/s13187-020-01751-z

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• Published: 14 May 2024

2023 summer warmth unparalleled over the past 2,000 years

• Jan Esper   ORCID: orcid.org/0000-0003-3919-014X 1 , 2 ,
• Max Torbenson   ORCID: orcid.org/0000-0003-2720-2238 1 &
• Ulf Büntgen 2 , 3 , 4  

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Including an exceptionally warm Northern Hemisphere (NH) summer 1 ,2 , 2023 has been reported as the hottest year on record 3-5 . Contextualizing recent anthropogenic warming against past natural variability is nontrivial, however, because the sparse 19 th century meteorological records tend to be too warm 6 . Here, we combine observed and reconstructed June-August (JJA) surface air temperatures to show that 2023 was the warmest NH extra-tropical summer over the past 2000 years exceeding the 95% confidence range of natural climate variability by more than half a degree Celsius. Comparison of the 2023 JJA warming against the coldest reconstructed summer in 536 CE reveals a maximum range of pre-Anthropocene-to-2023 temperatures of 3.93°C. Although 2023 is consistent with a greenhouse gases-induced warming trend 7 that is amplified by an unfolding El Niño event 8 , this extreme emphasizes the urgency to implement international agreements for carbon emission reduction.

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Department of Geography, Johannes Gutenberg University, Mainz, Germany

Jan Esper & Max Torbenson

Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

Jan Esper & Ulf Büntgen

Department of Geography, University of Cambridge, Cambridge, United Kingdom

Ulf Büntgen

Department of Geography, Masaryk University, Brno, Czech Republic

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Esper, J., Torbenson, M. & Büntgen, U. 2023 summer warmth unparalleled over the past 2,000 years. Nature (2024). https://doi.org/10.1038/s41586-024-07512-y

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DOI : https://doi.org/10.1038/s41586-024-07512-y

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Frontier AI Safety Commitments, AI Seoul Summit 2024

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The UK and Republic of Korea governments announced that the following organisations have agreed to the Frontier AI Safety Commitments:

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The above organisations, in furtherance of safe and trustworthy AI , undertake to develop and deploy their frontier AI models and systems [footnote 1] responsibly, in accordance with the following voluntary commitments, and to demonstrate how they have achieved this by publishing a safety framework focused on severe risks by the upcoming AI Summit in France.

Given the evolving state of the science in this area, the undersigned organisations’ approaches (as detailed in paragraphs I-VIII) to meeting Outcomes 1, 2 and 3 may evolve in the future. In such instances, organisations will provide transparency on this, including their reasons, through public updates. 

The above organisations also affirm their commitment to implement current best practices related to frontier AI safety, including: internal and external red-teaming of frontier AI models and systems for severe and novel threats; to work toward information sharing; to invest in cybersecurity and insider threat safeguards to protect proprietary and unreleased model weights; to incentivize third-party discovery and reporting of issues and vulnerabilities; to develop and deploy mechanisms that enable users to understand if audio or visual content is AI -generated; to publicly report model or system capabilities, limitations, and domains of appropriate and inappropriate use; to prioritize research on societal risks posed by frontier AI models and systems; and to develop and deploy frontier AI models and systems to help address the world’s greatest challenges.

Outcome 1. Organisations effectively identify, assess and manage risks when developing and deploying their frontier AI models and systems. They will:

I. Assess the risks posed by their frontier models or systems across the AI lifecycle, including before deploying that model or system, and, as appropriate, before and during training. Risk assessments should consider model capabilities and the context in which they are developed and deployed, as well as the efficacy of implemented mitigations to reduce the risks associated with their foreseeable use and misuse. They should also consider results from internal and external evaluations as appropriate, such as by independent third-party evaluators, their home governments [footnote 2] , and other bodies their governments deem appropriate.

II. Set out thresholds [footnote 3] at which severe risks posed by a model or system, unless adequately mitigated, would be deemed intolerable. Assess whether these thresholds have been breached, including monitoring how close a model or system is to such a breach. These thresholds should be defined with input from trusted actors, including organisations’ respective home governments as appropriate. They should align with relevant international agreements to which their home governments are party. They should also be accompanied by an explanation of how thresholds were decided upon, and by specific examples of situations where the models or systems would pose intolerable risk.

III. Articulate how risk mitigations will be identified and implemented to keep risks within defined thresholds, including safety and security-related risk mitigations such as modifying system behaviours and implementing robust security controls for unreleased model weights.

IV. Set out explicit processes they intend to follow if their model or system poses risks that meet or exceed the pre-defined thresholds. This includes processes to further develop and deploy their systems and models only if they assess that residual risks would stay below the thresholds. In the extreme, organisations commit not to develop or deploy a model or system at all, if mitigations cannot be applied to keep risks below the thresholds.

V. Continually invest in advancing their ability to implement commitments i-iv, including risk assessment and identification, thresholds definition, and mitigation effectiveness. This should include processes to assess and monitor the adequacy of mitigations, and identify additional mitigations as needed to ensure risks remain below the pre-defined thresholds. They will contribute to and take into account emerging best practice, international standards, and science on AI risk identification, assessment, and mitigation.

Outcome 2. Organisations are accountable for safely developing and deploying their frontier AI models and systems. They will:

VI. Adhere to the commitments outlined in I-V, including by developing and continuously reviewing internal accountability and governance frameworks and assigning roles, responsibilities and sufficient resources to do so.

Outcome 3. Organisations’ approaches to frontier AI safety are appropriately transparent to external actors, including governments. They will:

VII. Provide public transparency on the implementation of the above (I-VI), except insofar as doing so would increase risk or divulge sensitive commercial information to a degree disproportionate to the societal benefit. They should still share more detailed information which cannot be shared publicly with trusted actors, including their respective home governments or appointed body, as appropriate.

VIII. Explain how, if at all, external actors, such as governments, civil society, academics, and the public are involved in the process of assessing the risks of their AI models and systems, the adequacy of their safety framework (as described under I-VI), and their adherence to that framework.

We define ‘frontier AI ’ as highly capable general-purpose AI models or systems that can perform a wide variety of tasks and match or exceed the capabilities present in the most advanced models. References to AI models or systems in these commitments pertain to frontier AI models or systems only.  ↩

We define “home governments” as the government of the country in which the organisation is headquartered.  ↩

Thresholds can be defined using model capabilities, estimates of risk, implemented safeguards, deployment contexts and/or other relevant risk factors. It should be possible to assess whether thresholds have been breached.  ↩

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