Daniel X. Yang

31 papers receiving 708 citations

Daniel X. Yang'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

Daniel X. Yang
Comparison fields: 5 of 99
  • Health Informatics 142
  • Family Practice 33
  • Anesthesiology and Pain Medicine 32
  • Oncology 130
  • Health Information Management 14
Replace Jamil S. Samaan with:
Jamil S. Samaan United States
Christopher R. Manz United States
Avery Smith United States
Shalini Moningi United States
Marisa Cruz United States
Janice Newsome United States
Mark Arnold Australia
Ankur M. Doshi United States
Jayson S. Marwaha United States
Christian A. Nebiker Switzerland
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Citations per year

Countries citing papers authored by Daniel X. Yang

Since Specialization
Citations

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

Fields of papers citing papers by Daniel X. Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel X. Yang. 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 Daniel X. Yang. The network helps show where Daniel X. Yang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Large Language Model Influence on Diagnostic Reasoning
Hit paper breakdown →
2024239
2 201678
3 202178
4 201473
5
GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial
Hit paper breakdown →
202557
6 202041
7 202032
8 201930
9 201314
10 202414
11 201710
12 20238
13 20236
14 20095
15 20204
16 20204
17 20243
18 20242
19 20242
20 20232

About Daniel X. Yang

Daniel X. Yang is a scholar working on Pulmonary and Respiratory Medicine, Public Health, Environmental and Occupational Health, Molecular Biology, Oncology and Cancer Research, having authored 37 papers that have together received 718 indexed citations. Recurring topics across this work include Renal cell carcinoma treatment (4 papers), Cancer Genomics and Diagnostics (4 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Bladder and Urothelial Cancer Treatments (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Advanced Radiotherapy Techniques (2 papers), Machine Learning in Healthcare (2 papers) and Cervical Cancer and HPV Research (2 papers). The work is most often cited by research in Health Informatics (142 citations), Family Practice (33 citations), Anesthesiology and Pain Medicine (32 citations), Oncology (130 citations) and Health Information Management (14 citations). Daniel X. Yang has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include James B. Yu, Cary P. Gross, Pamela R. Soulos, Henry S. Park, Vikram Jairam, Jason Hom, Adam Rodman, Eric Strong, Andrew Olson and Eric Horvitz. Their work appears in journals such as Journal of Clinical Oncology, International Journal of Radiation Oncology*Biology*Physics, JAMA Network Open, JNCI Journal of the National Cancer Institute and Practical Radiation Oncology.

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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