Byron Crowe

16 papers receiving 517 citations

Hit Papers

Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge 2023 · 224 citations
2240+1+2Years since publication50100150200

Peers

Byron Crowe
Comparison fields: 5 of 83
  • Health Informatics 200
  • Family Practice 77
  • Pharmacy 37
  • Public Health, Environmental and Occupational Health 204
  • Health Information Management 21
Replace Vinyas Harish with:
Vinyas Harish Canada
Jackson Steinkamp United States
Atul Nakhasi United States
Susan Curtis United States
Victoria Goode United States
Friederike Holderried Germany
Laura Shafner United States
Gwendolyn C. Murphy United States
Muhammad Saqib Pakistan
Joseph Alexander Paguio United States
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Countries citing papers authored by Byron Crowe

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

16 of 16 papers shown
#Work
1
Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge
Hit paper breakdown →
2023224
2 2013109
3
Preliminary trial of the effect of general practice based nutritional advice.
199072
4 202457
5 202017
6 202117
7 202114
8 20226
9 20255
10 20204
11 20233
12
Computational and synthetic studies towards improving rescinnamine as an inducer of MSH2-dependent apoptosis in cancer treatment.
20132
13 20241
14 20201
15 20241
16 20211

About Byron Crowe

Byron Crowe is a scholar working on Health Informatics, Epidemiology, Artificial Intelligence, Pharmacy and Endocrinology, Diabetes and Metabolism, having authored 16 papers that have together received 534 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (4 papers), Obesity and Health Practices (3 papers), Machine Learning in Healthcare (3 papers), Diabetes Management and Education (2 papers), Health Policy Implementation Science (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers), Systemic Lupus Erythematosus Research (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Health Informatics (200 citations), Family Practice (77 citations), Pharmacy (37 citations), Public Health, Environmental and Occupational Health (204 citations) and Health Information Management (21 citations). Byron Crowe has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Adam Rodman, Zahir Kanjee, Juan M. Bustamante, Rick L. Tarleton, J I Mann, John A. Baron, Ray E. Gleason, Raja-Elie E. Abdulnour, Philip Wilson and Stephanie Cabral. Their work appears in journals such as Annals of the Rheumatic Diseases, Journal of Hospital Medicine, JAMA Internal Medicine, BMJ Quality & Safety and Clinics in Perinatology.

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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