Alvin Rajkomar

8.6k total citations · 2 hit papers
23 papers, 3.1k citations indexed

About

Alvin Rajkomar is a scholar working on General Health Professions, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Alvin Rajkomar has authored 23 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in General Health Professions, 8 papers in Artificial Intelligence and 5 papers in Health Information Management. Recurrent topics in Alvin Rajkomar's work include Machine Learning in Healthcare (5 papers), Healthcare cost, quality, practices (4 papers) and Topic Modeling (3 papers). Alvin Rajkomar is often cited by papers focused on Machine Learning in Healthcare (5 papers), Healthcare cost, quality, practices (4 papers) and Topic Modeling (3 papers). Alvin Rajkomar collaborates with scholars based in United States, Switzerland and Russia. Alvin Rajkomar's co-authors include Jay B. Dean, Isaac S. Kohane, Michaela Hardt, Marshall H. Chin, Greg S. Corrado, Michael Howell, Andrew Taylor, John Mongan, Victoria Valencia and Gurpreet Dhaliwal and has published in prestigious journals such as New England Journal of Medicine, Nature Communications and Annals of Internal Medicine.

In The Last Decade

Alvin Rajkomar

23 papers receiving 3.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine Learning in Medicine

2019 2.1k citations Alvin Rajkomar, Jay B. Dean et al. New England Journal of Medicine profile →
Ensuring Fairness in Machine Learning to Advance Health Equity

2018 551 citations Alvin Rajkomar, Michaela Hardt et al. Annals of Internal Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Alvin Rajkomar United States	14	959	880	727	456	321	23	3.1k
Richard A. Taylor United States	24	1.3k 1.4×	863 1.0×	823 1.1×	238 0.5×	232 0.7×	105	3.4k
Suchi Saria United States	27	942 1.0×	1.3k 1.5×	486 0.7×	691 1.5×	383 1.2×	80	4.0k
Fei Jiang United States	10	1.1k 1.1×	728 0.8×	792 1.1×	458 1.0×	207 0.6×	31	2.7k
Sally L. Baxter United States	20	879 0.9×	532 0.6×	854 1.2×	382 0.8×	406 1.3×	124	2.7k
Yilong Wang China	19	1.1k 1.1×	744 0.8×	760 1.0×	472 1.0×	233 0.7×	90	3.9k
Marzyeh Ghassemi United States	33	1.8k 1.9×	2.1k 2.4×	951 1.3×	533 1.2×	438 1.4×	111	4.8k
Kun‐Hsing Yu United States	28	970 1.0×	1.2k 1.4×	1.3k 1.8×	316 0.7×	369 1.1×	58	4.2k
Jie Ma China	22	607 0.6×	744 0.8×	485 0.7×	293 0.6×	206 0.6×	120	3.2k
Christopher Kelly United Kingdom	28	729 0.8×	481 0.5×	943 1.3×	208 0.5×	354 1.1×	123	3.7k
Jenna Wiens United States	26	552 0.6×	775 0.9×	396 0.5×	298 0.7×	222 0.7×	81	2.4k

Countries citing papers authored by Alvin Rajkomar

Since Specialization

Citations

This map shows the geographic impact of Alvin Rajkomar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alvin Rajkomar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alvin Rajkomar more than expected).

Fields of papers citing papers by Alvin Rajkomar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alvin Rajkomar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alvin Rajkomar. The network helps show where Alvin Rajkomar may publish in the future.

Co-authorship network of co-authors of Alvin Rajkomar

This figure shows the co-authorship network connecting the top 25 collaborators of Alvin Rajkomar. A scholar is included among the top collaborators of Alvin Rajkomar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alvin Rajkomar. Alvin Rajkomar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Schuster, Tal, et al.. (2023). SDOH-NLI: a Dataset for Inferring Social Determinants of Health from Clinical Notes. 4789–4798. 1 indexed citations

Rajkomar, Alvin, Yuchen Liu, Ming‐Jun Chen, et al.. (2022). Deciphering clinical abbreviations with a privacy protecting machine learning system. Nature Communications. 13(1). 7456–7456. 10 indexed citations

Rajkomar, Alvin, Jay B. Dean, & Isaac S. Kohane. (2019). Machine Learning in Medicine. New England Journal of Medicine. 380(14). 1347–1358. 2069 indexed citations breakdown →

Rajkomar, Alvin, et al.. (2019). Improved Patient Classification with Language Model Pretraining Over Clinical Notes.. arXiv (Cornell University). 2 indexed citations

Rajkomar, Alvin, Anjuli Kannan, Kai Chen, et al.. (2019). Automatically Charting Symptoms From Patient-Physician Conversations Using Machine Learning. JAMA Internal Medicine. 179(6). 836–836. 36 indexed citations

Rajkomar, Alvin, Michaela Hardt, Michael Howell, Greg S. Corrado, & Marshall H. Chin. (2018). Ensuring Fairness in Machine Learning to Advance Health Equity. Annals of Internal Medicine. 169(12). 866–872. 551 indexed citations breakdown →

Kannan, Anjuli, et al.. (2018). Semi-supervised Learning for Information Extraction from Dialogue. 2077–2081. 10 indexed citations

Rajkomar, Alvin, Andrew M. Dai, Mimi Sun, et al.. (2018). Reply: metrics to assess machine learning models. npj Digital Medicine. 1(1). 57–57. 16 indexed citations

Rajkomar, Alvin, James D. Harrison, Priya A. Prasad, et al.. (2018). Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial. BMJ Quality & Safety. 27(9). 691–699. 21 indexed citations

10.

Rajkomar, Alvin, et al.. (2017). What Happened to My Patient? An Educational Intervention to Facilitate Postdischarge Patient Follow-Up. Journal of Graduate Medical Education. 9(5). 627–633. 13 indexed citations

11.

Gonzales, Ralph, Christopher Moriates, Catherine Y. Lau, et al.. (2017). Caring Wisely: A Program to Support Frontline Clinicians and Staff in Improving Healthcare Delivery and Reducing Costs. Journal of Hospital Medicine. 12(8). 662–667. 11 indexed citations

12.

Rushakoff, Robert J, Mary M. Sullivan, Arti D. Shah, et al.. (2017). Association Between a Virtual Glucose Management Service and Glycemic Control in Hospitalized Adult Patients. Annals of Internal Medicine. 166(9). 621–627. 56 indexed citations

13.

Monash, Bradley, Nader Najafi, Michelle Mourad, et al.. (2017). Standardized Attending Rounds to Improve the Patient Experience: A Pragmatic Cluster Randomized Controlled Trial. Journal of Hospital Medicine. 12(3). 143–149. 30 indexed citations

14.

Rajkomar, Alvin, et al.. (2016). Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning. JMIR Medical Informatics. 4(4). e29–e29. 21 indexed citations

15.

Greysen, S. Ryan, et al.. (2016). Using Tablet Computers to Increase Patient Engagement With Electronic Personal Health Records: Protocol For a Prospective, Randomized Interventional Study. JMIR Research Protocols. 5(3). e176–e176. 10 indexed citations

16.

Rajkomar, Alvin, Charles E. McCulloch, & Margaret C. Fang. (2016). Low Diagnostic Utility of Rechecking Hemoglobins Within 24 Hours in Hospitalized Patients. The American Journal of Medicine. 129(11). 1194–1197. 5 indexed citations

17.

Zygourakis, Corinna C., Victoria Valencia, Christopher Moriates, et al.. (2016). Association Between Surgeon Scorecard Use and Operating Room Costs. JAMA Surgery. 152(3). 284–284. 85 indexed citations

18.

Rajkomar, Alvin, Sumant R Ranji, & Bradley A. Sharpe. (2016). Using the Electronic Health Record to Identify Educational Gaps for Internal Medicine Interns. Journal of Graduate Medical Education. 9(1). 109–112. 15 indexed citations

19.

Rajkomar, Alvin, et al.. (2016). High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks. Journal of Digital Imaging. 30(1). 95–101. 100 indexed citations

20.

Rajkomar, Alvin, et al.. (2015). The association between discharge before noon and length of stay in medical and surgical patients. Journal of Hospital Medicine. 11(12). 859–861. 29 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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