Isaac S. Kohane

66.5k total citations · 19 hit papers
470 papers, 34.8k citations indexed

About

Isaac S. Kohane is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Isaac S. Kohane has authored 470 papers receiving a total of 34.8k indexed citations (citations by other indexed papers that have themselves been cited), including 175 papers in Molecular Biology, 111 papers in Genetics and 67 papers in Artificial Intelligence. Recurrent topics in Isaac S. Kohane's work include Biomedical Text Mining and Ontologies (52 papers), Genomics and Rare Diseases (51 papers) and Gene expression and cancer classification (48 papers). Isaac S. Kohane is often cited by papers focused on Biomedical Text Mining and Ontologies (52 papers), Genomics and Rare Diseases (51 papers) and Gene expression and cancer classification (48 papers). Isaac S. Kohane collaborates with scholars based in United States, Israel and China. Isaac S. Kohane's co-authors include Andrew L. Beam, Atul J. Butte, Kun‐Hsing Yu, Alvin Rajkomar, Jay B. Dean, Kenneth D. Mandl, Susanne Churchill, Shawn N. Murphy, Griffin M. Weber and Vivian S. Gainer and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Isaac S. Kohane

459 papers receiving 33.8k citations

Hit Papers

Machine Learning in Medicine 1999 2026 2008 2017 2019 2018 2003 2004 2018 500 1000 1.5k 2.0k
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.

  1. Machine Learning in Medicine
    2019 2.1k citations Alvin Rajkomar, Jay B. Dean et al. New England Journal of Medicine profile →
  2. Artificial intelligence in healthcare
    2018 1.6k citations Kun‐Hsing Yu, Andrew L. Beam et al. profile →
  3. Coordinated reduction of genes of oxidative metabolism in humans with insulin resistance and diabetes: Potential role ofPGC1andNRF1
    2003 1.6k citations Isaac S. Kohane et al. Proceedings of the National Academy of Sciences profile →
  4. Gene regulation and DNA damage in the ageing human brain
    2004 1.4k citations Isaac S. Kohane et al. profile →
  5. Big Data and Machine Learning in Health Care
    2018 1.1k citations Andrew L. Beam, Isaac S. Kohane JAMA profile →
  6. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers
    2006 854 citations Isaac S. Kohane et al. profile →
  7. Safety of the BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting
    2021 672 citations Isaac S. Kohane, Ben Y. Reis et al. New England Journal of Medicine profile →
  8. MUTUAL INFORMATION RELEVANCE NETWORKS: FUNCTIONAL GENOMIC CLUSTERING USING PAIRWISE ENTROPY MEASUREMENTS
    1999 655 citations Isaac S. Kohane et al. profile →
  9. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2)
    2010 648 citations Shawn N. Murphy, Vivian S. Gainer et al. Journal of the American Medical Informatics Association profile →
  10. Effectiveness of a third dose of the BNT162b2 mRNA COVID-19 vaccine for preventing severe outcomes in Israel: an observational study
    2021 558 citations Isaac S. Kohane, Ben Y. Reis et al. profile →
  11. Adversarial attacks on medical machine learning
    2019 525 citations Andrew L. Beam, Isaac S. Kohane et al. profile →
  12. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records
    2016 463 citations Kenneth D. Mandl, Isaac S. Kohane et al. Journal of the American Medical Informatics Association profile →
  13. Genetic Misdiagnoses and the Potential for Health Disparities
    2016 461 citations Arjun K. Manrai, Peter Szolovits et al. New England Journal of Medicine profile →
  14. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study
    2018 415 citations Andrew L. Beam, Nathan Palmer et al. profile →
  15. The Co-Morbidity Burden of Children and Young Adults with Autism Spectrum Disorders
    2012 397 citations Isaac S. Kohane, Andrew McMurry et al. profile →
  16. Biases in electronic health record data due to processes within the healthcare system: retrospective observational study
    2018 232 citations Isaac S. Kohane et al. profile →
  17. Suicide Rates Among Adolescents and Young Adults in the United States, 2000-2017
    2019 213 citations Kun‐Hsing Yu, Isaac S. Kohane et al. JAMA profile →
  18. Effectiveness of the BNT162b2 mRNA COVID-19 vaccine in pregnancy
    2021 196 citations Isaac S. Kohane, Ben Y. Reis et al. profile →
  19. Causal machine learning for predicting treatment outcomes
    2024 95 citations Isaac S. Kohane et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Isaac S. Kohane United States 87 12.6k 5.0k 4.6k 3.4k 3.1k 470 34.8k
Joshua C. Denny United States 67 5.9k 0.5× 3.9k 0.8× 4.3k 0.9× 1.5k 0.4× 1.7k 0.6× 340 17.2k
Atul J. Butte United States 76 15.9k 1.3× 1.3k 0.3× 2.8k 0.6× 2.0k 0.6× 1.2k 0.4× 338 29.2k
Russ B. Altman United States 90 19.5k 1.6× 3.3k 0.7× 4.0k 0.9× 1.2k 0.3× 1.5k 0.5× 563 35.2k
Ewout W. Steyerberg Netherlands 133 4.4k 0.4× 4.1k 0.8× 2.4k 0.5× 16.6k 4.9× 5.2k 1.7× 1.1k 84.3k
Eric J. Topol United States 165 9.5k 0.8× 4.5k 0.9× 5.4k 1.2× 6.8k 2.0× 4.3k 1.4× 1.3k 113.9k
Andrew J. Vickers United States 102 4.9k 0.4× 1.5k 0.3× 1.0k 0.2× 4.0k 1.2× 2.9k 1.0× 748 48.7k
Gary S. Collins United Kingdom 85 1.6k 0.1× 4.1k 0.8× 995 0.2× 7.3k 2.2× 3.9k 1.3× 443 42.4k
Karel G.M. Moons Netherlands 99 1.6k 0.1× 4.2k 0.8× 1.2k 0.3× 10.0k 2.9× 4.2k 1.4× 469 54.1k
Jason H. Moore United States 76 12.6k 1.0× 2.5k 0.5× 8.5k 1.9× 1.6k 0.5× 846 0.3× 635 26.9k
Michael W. Kattan United States 121 7.0k 0.6× 1.7k 0.3× 1.3k 0.3× 3.1k 0.9× 1.6k 0.5× 807 52.8k

Countries citing papers authored by Isaac S. Kohane

Since Specialization
Citations

This map shows the geographic impact of Isaac S. Kohane'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 Isaac S. Kohane with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isaac S. Kohane more than expected).

Fields of papers citing papers by Isaac S. Kohane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Isaac S. Kohane. 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 Isaac S. Kohane. The network helps show where Isaac S. Kohane may publish in the future.

Co-authorship network of co-authors of Isaac S. Kohane

This figure shows the co-authorship network connecting the top 25 collaborators of Isaac S. Kohane. A scholar is included among the top collaborators of Isaac S. Kohane 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 Isaac S. Kohane. Isaac S. Kohane is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Manrai, Arjun K., David Ouyang, Joseph W. Hogan, & Isaac S. Kohane. (2025). Accelerating Science with Human+AI Review. NEJM AI. 2(12). 4 indexed citations
2.
Yuan, William, et al.. (2021). Illustrating potential effects of alternate control populations on real-world evidence-based statistical analyses. JAMIA Open. 4(2). ooab045–ooab045. 2 indexed citations
3.
Yu, Kun‐Hsing, Feiran Wang, Gerald J. Berry, et al.. (2020). Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks. Journal of the American Medical Informatics Association. 27(5). 757–769. 82 indexed citations
4.
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 →
5.
Liao, Katherine P., Jiehuan Sun, Tianrun Cai, et al.. (2019). High-throughput multimodal automated phenotyping (MAP) with application to PheWAS. Journal of the American Medical Informatics Association. 26(11). 1255–1262. 56 indexed citations
6.
Hutchison, Luke A. D., Bonnie Berger, & Isaac S. Kohane. (2019). Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation. Bioinformatics. 36(13). 4047–4057. 4 indexed citations
7.
Yuan, William, Kun‐Hsing Yu, Nathan Palmer, Fatima Cody Stanford, & Isaac S. Kohane. (2019). Evaluation of the association of bariatric surgery with subsequent depression. International Journal of Obesity. 43(12). 2528–2535. 14 indexed citations
8.
Beam, Andrew L. & Isaac S. Kohane. (2018). Big Data and Machine Learning in Health Care. JAMA. 319(13). 1317–1317. 1143 indexed citations breakdown →
9.
Ó'Dúshláine, Colm, Stephan Ripke, Douglas M. Ruderfer, et al.. (2014). Rare Copy Number Variation in Treatment-Resistant Major Depressive Disorder. Biological Psychiatry. 76(7). 536–541. 48 indexed citations
10.
McMurry, Andrew, et al.. (2013). Improved de-identification of physician notes through integrative modeling of both public and private medical text. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
11.
Mandl, Kenneth D. & Isaac S. Kohane. (2012). Escaping the EHR Trap — The Future of Health IT. New England Journal of Medicine. 366(24). 2240–2242. 121 indexed citations
12.
Liao, Katherine P., Tianxi Cai, Vivian S. Gainer, et al.. (2010). Electronic Medical Records for Discovery Research in Rheumatoid Arthritis. PubMed Central. 1 indexed citations
13.
Kho, Alvin T., Soumyaroop Bhattacharya, Kelan G. Tantisira, et al.. (2009). Transcriptomic Analysis of Human Lung Development. American Journal of Respiratory and Critical Care Medicine. 181(1). 54–63. 90 indexed citations
14.
Mandl, Kenneth D. & Isaac S. Kohane. (2008). Tectonic Shifts in the Health Information Economy. New England Journal of Medicine. 358(16). 1732–1737. 103 indexed citations
15.
Eisenberg, Iris, Alal Eran, Ichizo Nishino, et al.. (2007). Distinctive patterns of microRNA expression in primary muscular disorders. Proceedings of the National Academy of Sciences. 104(43). 17016–17021. 407 indexed citations
16.
Liu, Fenghua, Peter J. Park, Weil Lai, et al.. (2006). A Genome-Wide Screen Reveals Functional Gene Clusters in the Cancer Genome and Identifies EphA2 as a Mitogen in Glioblastoma. Cancer Research. 66(22). 10815–10823. 94 indexed citations
17.
Simons, William Walter, et al.. (2006). Integration of the Personally Controlled Electronic Medical Record into a Regional and Data Exchange: A National Demonstration.. American Medical Informatics Association Annual Symposium. 2006. 1099.
18.
Mandl, Kenneth D., Alberto Riva, & Isaac S. Kohane. (2000). A Distributed, Secure File System For Personal Medical Records. PubMed Central. 1075–1075. 2 indexed citations
19.
Bradshaw, Karen, Kenneth D. Mandl, & Isaac S. Kohane. (1998). HealthConnect: A Structured Communication System for Health Management. Europe PMC (PubMed Central). 979–979. 1 indexed citations
20.
Greenes, David S., et al.. (1998). An Alert System for ED Laboratory Test Results.. PubMed Central. 994–994. 1 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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