Po-Hsuan Cameron Chen

4.3k total citations · 1 hit paper
23 papers, 2.0k citations indexed

About

Po-Hsuan Cameron Chen is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Health Informatics. According to data from OpenAlex, Po-Hsuan Cameron Chen has authored 23 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Artificial Intelligence and 7 papers in Health Informatics. Recurrent topics in Po-Hsuan Cameron Chen's 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). Po-Hsuan Cameron Chen is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (13 papers) and Artificial Intelligence in Healthcare and Education (7 papers). Po-Hsuan Cameron Chen collaborates with scholars based in United States, United Kingdom and Austria. Po-Hsuan Cameron Chen's 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 and has published in prestigious journals such as Nature, JAMA and Nature Medicine.

In The Last Decade

Po-Hsuan Cameron Chen

23 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

2019 302 citations Kunal Nagpal, Davis Foote et al. npj Digital Medicine profile →

Peers

Countries citing papers authored by Po-Hsuan Cameron Chen

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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20 of 20 papers shown

#	Work	Indexed citations
1	Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer 2024 ·Modern Pathology ·Pok Fai Wong, (unknown), (unknown), (unknown), Charles Santori, (unknown), Andrew Homyk, Kunal Nagpal, (unknown), Ellery Wulczyn, Tadayuki Yoshitake, (unknown), David F. Steiner, Sudha Rao, Po-Hsuan Cameron Chen, (unknown), (unknown), Peter Cimermančič	4
2	Assessment of Pathology Domain-Specific Knowledge of ChatGPT and Comparison to Human Performance 2024 ·Archives of Pathology & Laboratory Medicine ·Andrew Y. Wang, (unknown), Christopher Tran, Robert Homer, (unknown), Joanna C. Walsh, (unknown), Irene Sansano, Snehal Sonawane, Vincent Cockenpot, Sanjay Mukhopadhyay, (unknown), (unknown), (unknown), (unknown), (unknown), Pallavi Mishra, (unknown), Po-Hsuan Cameron Chen, Matthew J. Cecchini	25
3	Evaluating ChatGPT’s competency in radiation oncology: A comprehensive assessment across clinical scenarios 2024 ·Radiotherapy and Oncology ·(unknown), (unknown), Po-Hsuan Cameron Chen, Glenn Bauman, Vikram Velker, Belal Ahmad, (unknown), (unknown), (unknown), (unknown)	3
4	Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning 2023 ·SHILAP Revista de lepidopterología ·Justin D. Krogue, Shekoofeh Azizi, Fraser Elisabeth Tan, (unknown), Trissia Brown, Markus Plass, Robert Reihs, Heimo Müller, Kurt Zatloukal, (unknown), Greg S. Corrado, Lily H. Peng, Craig H. Mermel, Yun Liu, Po-Hsuan Cameron Chen, Saurabh Gombar, Thomas J. Montine, Jeanne Shen, David F. Steiner, Ellery Wulczyn	12
5	Pathologist Validation of a Machine Learning–Derived Feature for Colon Cancer Risk Stratification 2023 ·JAMA Network Open ·Vincenzo L’Imperio, Ellery Wulczyn, Markus Plass, Heimo Müller, Nicolò Tamini, Luca Gianotti, Nicola Zucchini, Robert Reihs, Greg S. Corrado, Dale R. Webster, Lily H. Peng, Po-Hsuan Cameron Chen, Marialuisa Lavitrano, Yun Liu, David F. Steiner, Kurt Zatloukal, Fabio Pagni	31
6	Artificial Intelligence in a Structurally Unjust Society 2022 ·(unknown), Po-Hsuan Cameron Chen	16
7	Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images 2021 ·Scientific Reports ·Apaar Sadhwani, (unknown), Ali Behrooz, Trissia Brown, (unknown), (unknown), (unknown), (unknown), Fraser Elisabeth Tan, (unknown), Ellery Wulczyn, Eunhee S. Yi, Craig H. Mermel, Debra Hanks, Po-Hsuan Cameron Chen, Kimary Kulig, Cory Batenchuk, David F. Steiner, Peter Cimermančič	34
8	Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies—Current Status and Next Steps 2021 ·European Urology Focus ·Kimmo Kartasalo, Wouter Bulten, Brett Delahunt, Po-Hsuan Cameron Chen, Hans Pinckaers, Henrik Olsson, (unknown), (unknown), Hemamali Samaratunga, Toyonori Tsuzuki, Johan Lindberg, Mattias Rantalainen, Carolina Wählby, Geert Litjens, Pekka Ruusuvuori, Lars Egevad, Martin Eklund	31
9	Determining breast cancer biomarker status and associated morphological features using deep learning 2021 ·Communications Medicine ·Paul Gamble, Ronnachai Jaroensri, Hongwu Wang, Fraser Elisabeth Tan, Melissa Moran, Trissia Brown, (unknown), Emad A. Rakha, Michael S. Toss, David J. Dabbs, Peter Regitnig, Niels Olson, (unknown), (unknown), Greg S. Corrado, Lily H. Peng, Yun Liu, Craig H. Mermel, David F. Steiner, Po-Hsuan Cameron Chen	86
10	Evaluation of artificial intelligence on a reference standard based on subjective interpretation 2021 ·The Lancet Digital Health ·Po-Hsuan Cameron Chen, Craig H. Mermel, Yun Liu	33
11	Vulnerability of Antarctica’s ice shelves to meltwater-driven fracture 2020 ·Nature ·Ching‐Yao Lai, Jonathan Kingslake, Martin Wearing, Po-Hsuan Cameron Chen, Pierre Gentine, (unknown), Julian J. Spergel, Jan Melchior van Wessem	139
12	Closing the translation gap: AI applications in digital pathology 2020 ·Biochimica et Biophysica Acta (BBA) - Reviews on Cancer ·David F. Steiner, Po-Hsuan Cameron Chen, Craig H. Mermel	51
13	Deep learning-based survival prediction for multiple cancer types using histopathology images 2020 ·PLoS ONE ·Ellery Wulczyn, David F. Steiner, Zhaoyang Xu, Apaar Sadhwani, Hongwu Wang, (unknown), Craig H. Mermel, Po-Hsuan Cameron Chen, Yun Liu, Martin C. Stumpe	159
14	Current and future applications of artificial intelligence in pathology: a clinical perspective 2020 ·Journal of Clinical Pathology ·Emad A. Rakha, Michael S. Toss, Sho Shiino, Paul Gamble, Ronnachai Jaroensri, Craig H. Mermel, Po-Hsuan Cameron Chen	69
15	How to develop machine learning models for healthcare 2019 ·Nature Materials ·Po-Hsuan Cameron Chen, Yun Liu, Lily Peng	182
16	Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer breakdown → 2019 ·npj Digital Medicine ·Kunal Nagpal, Davis Foote, Yun Liu, Po-Hsuan Cameron Chen, Ellery Wulczyn, Fraser Elisabeth Tan, Niels Olson, Jenny L. Smith, Arash Mohtashamian, (unknown), Greg S. Corrado, Robert MacDonald, Lily H. Peng, Mahul B. Amin, Andrew Evans, Ankur R. Sangoi, Craig H. Mermel, Jason Hipp, Martin C. Stumpe	302
17	Artificial intelligence in digital breast pathology: Techniques and applications 2019 ·The Breast ·Asmaa Ibrahim, Paul Gamble, Ronnachai Jaroensri, Mohammed M. Abdelsamea, Craig H. Mermel, Po-Hsuan Cameron Chen, Emad A. Rakha	122
18	An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis 2019 ·Nature Medicine ·Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, Yun Liu, Shiro Kadowaki, Kunal Nagpal, Timo Kohlberger, Jay B. Dean, Greg S. Corrado, Jason Hipp, Craig H. Mermel, Martin C. Stumpe	186
19	Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection 2019 ·Journal of Pathology Informatics ·Timo Kohlberger, Yun Liu, Melissa Moran, Po-Hsuan Cameron Chen, Trissia Brown, Jason Hipp, Craig H. Mermel, Martin C. Stumpe	61
20	Reply: ‘The importance of study design in the application of artificial intelligence methods in medicine’ 2019 ·npj Digital Medicine ·Kunal Nagpal, Yun Liu, Po-Hsuan Cameron Chen, Martin C. Stumpe, Craig H. Mermel	1

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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