David Kim

63 papers receiving 2.3k citations

David Kim's Hit Papers

An evaluation framework for clinical use of large language models in patient interaction tasks 2025 · 66 citations
660+2+4Years since publication100200300400500

Peers

David Kim
Comparison fields: 5 of 162
  • Health Informatics 47
  • Applied Microbiology and Biotechnology 48
  • Pathology and Forensic Medicine 399
  • Infectious Diseases 343
  • Cognitive Neuroscience 362
Replace Clare Davenport with:
Clare Davenport United Kingdom
Patrick Ip Hong Kong
Chiara Bovo Italy
Rebecca Voelker United States
Mondher Toumi France
Thomas Fanshawe United Kingdom
Roberta Pastorino Italy
Brian T. Garibaldi United States
Michael L. Gross United States
Matt Vassar United States
David Kim relative to Clare Davenport United Kingdom Clare Davenport's profile →
Citations per field
00.5×9.7×
Clare Davenport · 1×
Citations per year

Countries citing papers authored by David Kim

Since Specialization
Citations

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

Fields of papers citing papers by David Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Kim, 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 David Kim Line = papers co-authored together David Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Rates of Co-infection Between SARS-CoV-2 and Other Respiratory Pathogens
Hit paper breakdown →
2020510
2 2009462
3 2003410
4 2015225
5 1997111
6
An evaluation framework for clinical use of large language models in patient interaction tasks
Hit paper breakdown →
202566
7 201441
8 201240
9 201640
10 199740
11 201540
12 201732
13 201531
14 200026
15 202325
16 202325
17 200921
18 202018
19 201717
20 202217

About David Kim

David Kim is a scholar working on Surgery, Epidemiology, Emergency Medicine, Health and Neurology, having authored 79 papers that have together received 2.4k indexed citations. Recurring topics across this work include Emergency and Acute Care Studies (5 papers), COVID-19 Clinical Research Studies (3 papers), Trauma and Emergency Care Studies (3 papers), Scoliosis diagnosis and treatment (3 papers), Social Media in Health Education (3 papers), Health Literacy and Information Accessibility (3 papers), Cardiac Arrest and Resuscitation (3 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). The work is most often cited by research in Health Informatics (47 citations), Applied Microbiology and Biotechnology (48 citations), Pathology and Forensic Medicine (399 citations), Infectious Diseases (343 citations) and Cognitive Neuroscience (362 citations). David Kim has collaborated with scholars based in United States, Canada and Hong Kong. Frequent co-authors include Eugene J. Carragee, Adam K. Anderson, Joshua M. Susskind, Hanah A. Chapman, Ian Brown, James Quinn, Patrick W. Suen, Benjamin A. Pinsky, Nigam H. Shah and Nicholas A. Christakis. Their work appears in journals such as Annals of Emergency Medicine, PLoS ONE, Journal of the Association for Information Systems, Pediatric Dermatology and npj Digital Medicine.

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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