Kun‐Hsing Yu

58 papers receiving 4.7k citations

Kun‐Hsing Yu's Hit Papers

A vision–language foundation model for precision oncology 2025 · 75 citations
750+3+6Years since publication50010001.5k

Peers

Kun‐Hsing Yu
Comparison fields: 5 of 185
  • Health Informatics 1.0k
  • Health Information Management 318
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Artificial Intelligence 1.2k
  • Family Practice 49
Replace Hao Li with:
Hao Li China
Marc Coram United States
Euan A. Ashley United States
Alastair K. Denniston United Kingdom
Eric K. Oermann United States
Yi Dong China
Alvin Rajkomar United States
Xiaoxuan Liu United Kingdom
Marzyeh Ghassemi United States
Pearse A. Keane United Kingdom
Kun‐Hsing Yu relative to Hao Li China Hao Li's profile →
Citations per field
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Hao Li · 1×
Citations per year

Countries citing papers authored by Kun‐Hsing Yu

Since Specialization
Citations

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

Fields of papers citing papers by Kun‐Hsing Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kun‐Hsing Yu. 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 Kun‐Hsing Yu. The network helps show where Kun‐Hsing Yu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Artificial intelligence in healthcare
Hit paper breakdown →
20181888
2
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
Hit paper breakdown →
2016729
3
Suicide Rates Among Adolescents and Young Adults in the United States, 2000-2017
Hit paper breakdown →
2019224
4 2018162
5 2016124
6 2019113
7 201689
8 201188
9 201986
10 202086
11 201781
12
A vision–language foundation model for precision oncology
Hit paper breakdown →
202575
13 202469
14 201566
15 202162
16 202159
17 201152
18 201151
19 202050
20 202146

About Kun‐Hsing Yu

Kun‐Hsing Yu is a scholar working on Artificial Intelligence, Molecular Biology, Oncology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 63 papers that have together received 4.9k indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Cancer Immunotherapy and Biomarkers (8 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Bioinformatics and Genomic Networks (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Cutaneous Melanoma Detection and Management (3 papers), Advanced Proteomics Techniques and Applications (3 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Health Informatics (1.0k citations), Health Information Management (318 citations), Radiology, Nuclear Medicine and Imaging (1.1k citations), Artificial Intelligence (1.2k citations) and Family Practice (49 citations). Kun‐Hsing Yu has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Isaac S. Kohane, Andrew L. Beam, M Snyder, Russ B. Altman, Christopher Ré, Gerald J. Berry, Daniel L. Rubin, Ce Zhang, Oren Miron and Rachel Wilf‐Miron. Their work appears in journals such as Journal of Proteome Research, Academic Medicine, Molecular & Cellular Proteomics, Journal of Clinical Oncology and Journal of the American Medical Informatics Association.

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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