Po-Hsuan Cameron Chen
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Health Informatics top 0.1%
- Pulmonary and Respiratory Medicine top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Yun LiuLily PengCraig H. MermelJonathan KrauseMartin C. StumpeDavid F. SteinerGreg S. CorradoJason Hipp
- Topics
- Radiomics and Machine Learning in Medical Imaging (15 papers)AI in cancer detection (13 papers)Artificial Intelligence in Healthcare and Education (7 papers)
- Journals
- NatureJAMANature Medicine
- Partner nations
- United StatesUnited KingdomAustria
In The Last Decade
Po-Hsuan Cameron Chen
23 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Artificial Intelligence 986
- Radiology, Nuclear Medicine and Imaging 931
- Health Informatics 438
- Pulmonary and Respiratory Medicine 367
- Computer Vision and Pattern Recognition 235
Countries citing papers authored by Po-Hsuan Cameron Chen
This map shows the geographic impact of Po-Hsuan Cameron Chen'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 Po-Hsuan Cameron Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Po-Hsuan Cameron Chen more than expected).
Fields of papers citing papers by Po-Hsuan Cameron Chen
This network shows the impact of papers produced by Po-Hsuan Cameron Chen. 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 Po-Hsuan Cameron Chen. The network helps show where Po-Hsuan Cameron Chen may publish in the future.
Co-authorship network of co-authors of Po-Hsuan Cameron Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Po-Hsuan Cameron Chen. A scholar is included among the top collaborators of Po-Hsuan Cameron Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Po-Hsuan Cameron Chen. Po-Hsuan Cameron Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 25 | |
| 3 | 3 | |
| 4 | 12 | |
| 5 | 31 | |
| 6 | 16 | |
| 7 | 34 | |
| 8 | 31 | |
| 9 | 86 | |
| 10 | 33 | |
| 11 | 139 | |
| 12 | 51 | |
| 13 | 159 | |
| 14 | 69 | |
| 15 | 182 | |
| 16 | Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancerbreakdown → | 302 |
| 17 | 122 | |
| 18 | 186 | |
| 19 | 61 | |
| 20 | 1 |
About Po-Hsuan Cameron Chen
Po-Hsuan Cameron Chen is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Family Practice, having authored 23 papers that have together received 2.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (13 papers) and Artificial Intelligence in Healthcare and Education (7 papers). The work is most often cited by research in Health Informatics (438 citations), Radiology, Nuclear Medicine and Imaging (931 citations) and Artificial Intelligence (986 citations). Po-Hsuan Cameron Chen has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include Yun Liu, Lily Peng, Craig H. Mermel, Jonathan Krause, Martin C. Stumpe, David F. Steiner, Greg S. Corrado, Jason Hipp, Ellery Wulczyn and Kunal Nagpal. Their work appears in journals such as Nature, JAMA and Nature 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.