Eric Strong

993 citations
7 papers · 422 · 2 hit papers · h-index 4

Impact in

Papers in

Eric Strong

5 papers receiving 413 citations

Eric Strong's Hit Papers

GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial 2025 · 57 citations
570+1Years since publication50100150200

Peers

Eric Strong
Comparison fields: 5 of 76
  • Health Informatics 203
  • Family Practice 46
  • Health Information Management 15
  • Artificial Intelligence 69
  • Radiology, Nuclear Medicine and Imaging 36
Replace Teresa Festl‐Wietek with:
Teresa Festl‐Wietek Germany
Dana Brin Israel
Poonam Hosamani United States
Brian C. Gin United States
Robert Kaczmarczyk Germany
Felipe Morgado Canada
Masashi Yokose Japan
Joel Grunhut United States
Hussein Uraiby United Kingdom
Eric Strong relative to Teresa Festl‐Wietek Germany Teresa Festl‐Wietek's profile →
Citations per field
00.5×1.5×
Teresa Festl‐Wietek · 1×
Citations per year

Countries citing papers authored by Eric Strong

Since Specialization
Citations

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

Fields of papers citing papers by Eric Strong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1
Large Language Model Influence on Diagnostic Reasoning
Hit paper breakdown →
2024239
2 2023108
3
GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial
Hit paper breakdown →
202557
4 202115
5 20203
6 20240
7 20260

About Eric Strong

Eric Strong is a scholar working on Family Practice, Health Informatics, Psychiatry and Mental health, Cardiology and Cardiovascular Medicine and Public Health, Environmental and Occupational Health, having authored 7 papers that have together received 422 indexed citations. Recurring topics across this work include Clinical Reasoning and Diagnostic Skills (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Migraine and Headache Studies (2 papers), Cardiac, Anesthesia and Surgical Outcomes (1 paper), Education and Critical Thinking Development (1 paper), Innovative Teaching and Learning Methods (1 paper), Biochemical effects in animals (1 paper) and Innovations in Medical Education (1 paper). The work is most often cited by research in Health Informatics (203 citations), Family Practice (46 citations), Health Information Management (15 citations), Artificial Intelligence (69 citations) and Radiology, Nuclear Medicine and Imaging (36 citations). Eric Strong has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Jason Hom, Jonathan H. Chen, Yingjie Weng, Andrew S. Parsons, Zahir Kanjee, Adam Rodman, Eric Horvitz, Daniel X. Yang, Hannah Kerman and Ethan Goh. Their work appears in journals such as Nature Medicine, JAMA Network Open, JAMA Internal Medicine, Journal of Child Neurology 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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