Byron Crowe
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Family Practice top 5%
- Clinical Reasoning and Diagnostic Skills
Papers in
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- Artificial Intelligence in Healthcare and Education 4
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- Machine Learning in Healthcare 3
- Co-authors
- Adam Rodman (4 shared papers)Zahir Kanjee (2 shared papers)Rick L. Tarleton (1 shared paper)Juan M. Bustamante (1 shared paper)John A. Baron (1 shared paper)J I Mann (1 shared paper)Ray E. Gleason (1 shared paper)Raja-Elie E. Abdulnour (2 shared papers)
- Journals
- Journal of Hospital Medicine (2 papers)JAMA Internal Medicine (2 papers)Annals of the Rheumatic Diseases (2 papers)The Journal of Infectious Diseases (1 paper)JAMA (1 paper)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Byron Crowe
15 papers receiving 568 citations
Byron Crowe's Hit Papers
Peers
Comparison fields: 5 of 76
- Health Informatics 197
- Family Practice 49
- Public Health, Environmental and Occupational Health 143
- Epidemiology 126
- Pharmacy 17
Countries citing papers authored by Byron Crowe
This map shows the geographic impact of Byron Crowe'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 Byron Crowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Byron Crowe more than expected).
Fields of papers citing papers by Byron Crowe
This network shows the impact of papers produced by Byron Crowe. 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 Byron Crowe. The network helps show where Byron Crowe may publish in the future.
Co-authors
The 25 scholars most cited alongside Byron Crowe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge Hit paper breakdown → | 2023 | 253 |
| 2 | 2013 | 111 | |
| 3 | 2024 | 73 | |
| 4 | Preliminary trial of the effect of general practice based nutritional advice. | 1990 | 72 |
| 5 | 2021 | 18 | |
| 6 | 2020 | 17 | |
| 7 | 2021 | 14 | |
| 8 | 2025 | 9 | |
| 9 | 2022 | 6 | |
| 10 | 2020 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2024 | 2 | |
| 13 | 2021 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2020 | 1 |
About Byron Crowe
Byron Crowe is a scholar working on Health Informatics, Artificial Intelligence, General Health Professions, Family Practice and Epidemiology, having authored 15 papers that have together received 586 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (4 papers), Machine Learning in Healthcare (3 papers), Health Policy Implementation Science (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Obesity and Health Practices (2 papers), Systemic Lupus Erythematosus Research (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers) and Trypanosoma species research and implications (1 paper). The work is most often cited by research in Health Informatics (197 citations), Family Practice (49 citations), Public Health, Environmental and Occupational Health (143 citations), Epidemiology (126 citations) and Pharmacy (17 citations). Byron Crowe has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Adam Rodman, Zahir Kanjee, Rick L. Tarleton, Juan M. Bustamante, John A. Baron, J I Mann, Ray E. Gleason, Raja-Elie E. Abdulnour, Philip Wilson and Stephanie Cabral. Their work appears in journals such as Journal of Hospital Medicine, JAMA Internal Medicine, Annals of the Rheumatic Diseases, The Journal of Infectious Diseases and JAMA.
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.