Ethan Goh

849 citations
10 papers · 325 · 2 hit papers · h-index 6

Impact in

Papers in

Ethan Goh

9 papers receiving 307 citations

Hit Papers

GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial 2025 · 35 citations
350+1Years since publication50100150

Peers

Ethan Goh
Comparison fields: 5 of 81
  • Health Informatics 119
  • Family Practice 34
  • Otorhinolaryngology 21
  • Health Information Management 13
  • Oncology 76
Replace Asitava Deb Roy with:
Asitava Deb Roy India
Mary Sun United States
Priya Manjaly United States
Kenneth L. Abbott United States
Nita Valikodath United States
Cherry Sit United Kingdom
Louis Cai United States
Howard Grundy United States
Simon Ronicke Germany
Tobias E. Sangers Netherlands
Ethan Goh relative to Asitava Deb Roy India Asitava Deb Roy's profile →
Citations per field
00.5×10×16×
Asitava Deb Roy · 1×
Citations per year

Countries citing papers authored by Ethan Goh

Since Specialization
Citations

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

Fields of papers citing papers by Ethan Goh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1
Large Language Model Influence on Diagnostic Reasoning
Hit paper breakdown →
2024167
2 197662
3
GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial
Hit paper breakdown →
202535
4 197626
5 197921
6 20136
7 20255
8 20232
9 19741
10 20250

About Ethan Goh

Ethan Goh is a scholar working on Oncology, Family Practice, Otorhinolaryngology, Public Health, Environmental and Occupational Health and Radiology, Nuclear Medicine and Imaging, having authored 10 papers that have together received 325 indexed citations. Recurring topics across this work include Clinical Reasoning and Diagnostic Skills (3 papers), Viral-associated cancers and disorders (2 papers), Head and Neck Cancer Studies (2 papers), Innovations in Medical Education (2 papers), Immune Cell Function and Interaction (1 paper), Microbial infections and disease research (1 paper), Cytomegalovirus and herpesvirus research (1 paper) and Blood groups and transfusion (1 paper). The work is most often cited by research in Health Informatics (119 citations), Family Practice (34 citations), Otorhinolaryngology (21 citations), Health Information Management (13 citations) and Oncology (76 citations). Ethan Goh has collaborated with scholars based in United States, Singapore and Switzerland. Frequent co-authors include S. H. Chan, K. Shanmugaratnam, Michael Simons, Arnold Milstein, Jonathan H. Chen, Daniel X. Yang, Eric Horvitz, Eric Strong, Yingjie Weng and Andrew S. Parsons. Their work appears in journals such as International Journal of Cancer, Nature Medicine, Journal of Clinical Oncology, npj Digital Medicine and JAMA Network Open.

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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