Jason Hom

115 papers receiving 3.3k citations

Jason Hom's Hit Papers

GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial 2025 · 82 citations
820+1Years since publication100200300400

Peers

Jason Hom
Comparison fields: 5 of 160
  • Health Informatics 403
  • Family Practice 74
  • Health Information Management 114
  • Aging 31
  • Internal Medicine 54
Replace Joseph B. Leader with:
Joseph B. Leader United States
Pooja Rao United States
Paul N. Cooper United Kingdom
James Matcham United Kingdom
Michelle Turcotte Canada
Lisa Bastarache United States
David B. Kurland United States
Nathan E. Wineinger United States
Clement Chee Yung Tham Hong Kong
R Thomas Lumbers United Kingdom
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Countries citing papers authored by Jason Hom

Since Specialization
Citations

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

Fields of papers citing papers by Jason Hom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason Hom. 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 Jason Hom. The network helps show where Jason Hom may publish in the future.

Co-authors

The 25 scholars most cited alongside Jason Hom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jason Hom Line = papers co-authored together Jason Hom links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 121 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Adapted large language models can outperform medical experts in clinical text summarization
Hit paper breakdown →
2024405
2
Large Language Model Influence on Diagnostic Reasoning
Hit paper breakdown →
2024330
3 2009158
4 2010137
5 2023119
6 201884
7 202184
8
GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial
Hit paper breakdown →
202582
9 201880
10 201976
11 201870
12 201267
13 201862
14 202056
15 200854
16 201953
17 202050
18 201949
19 202047
20 201544

About Jason Hom

Jason Hom is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Cell Biology and Cardiology and Cardiovascular Medicine, having authored 121 papers that have together received 3.3k indexed citations. Recurring topics across this work include Genomics and Rare Diseases (11 papers), Acute Ischemic Stroke Management (8 papers), MRI in cancer diagnosis (6 papers), Cellular transport and secretion (6 papers), Genetics and Neurodevelopmental Disorders (6 papers), RNA Research and Splicing (5 papers), Cerebrovascular and Carotid Artery Diseases (5 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Health Informatics (403 citations), Family Practice (74 citations), Health Information Management (114 citations), Aging (31 citations) and Internal Medicine (54 citations). Jason Hom has collaborated with scholars based in United States, Italy and Netherlands. Frequent co-authors include Jonathan H. Chen, Max Wintermark, Neera K. Ahuja, Joerg Bredno, Yingjie Weng, Poonam Hosamani, Eric Strong, Thomas Schneider, Jan Willem Dankbaar and Bruno Passebon Soares. Their work appears in journals such as The American Journal of Human Genetics, Genetics in Medicine, Journal of General Internal Medicine, Journal of Hospital Medicine and Journal of the American College of Radiology.

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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