Richard E. Fan

2.4k total citations
79 papers, 1.5k citations indexed

About

Richard E. Fan is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Richard E. Fan has authored 79 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Pulmonary and Respiratory Medicine, 35 papers in Radiology, Nuclear Medicine and Imaging and 21 papers in Biomedical Engineering. Recurrent topics in Richard E. Fan's work include Prostate Cancer Diagnosis and Treatment (45 papers), Radiomics and Machine Learning in Medical Imaging (28 papers) and Prostate Cancer Treatment and Research (18 papers). Richard E. Fan is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (45 papers), Radiomics and Machine Learning in Medical Imaging (28 papers) and Prostate Cancer Treatment and Research (18 papers). Richard E. Fan collaborates with scholars based in United States, Denmark and United Kingdom. Richard E. Fan's co-authors include Geoffrey A. Sonn, James D. Brooks, Pejman Ghanouni, Christian A. Kunder, Mirabela Rusu, Andreas M. Loening, Michael B. Sano, Lei Xing, Martin O. Culjat and Warren S. Grundfest and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer and Scientific Reports.

In The Last Decade

Richard E. Fan

73 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Richard E. Fan United States 22 662 522 407 217 159 79 1.5k
Javier A. Jo United States 29 418 0.6× 651 1.2× 1.1k 2.7× 60 0.3× 132 0.8× 126 2.1k
Máté E. Maros Germany 12 127 0.2× 266 0.5× 155 0.4× 195 0.9× 182 1.1× 43 906
Toshihiro Nishimura Japan 16 170 0.3× 124 0.2× 237 0.6× 41 0.2× 82 0.5× 135 1.2k
Guanglei Zhang China 26 205 0.3× 841 1.6× 981 2.4× 195 0.9× 211 1.3× 116 1.9k
Donald J. Peck United States 21 344 0.5× 1.1k 2.1× 269 0.7× 126 0.6× 78 0.5× 45 1.6k
Ahmed Soliman United States 22 516 0.8× 1.2k 2.4× 245 0.6× 335 1.5× 79 0.5× 109 2.0k
Michael Friebe Germany 17 223 0.3× 316 0.6× 290 0.7× 177 0.8× 37 0.2× 146 1.1k
Kazuko Itoh Japan 24 108 0.2× 157 0.3× 151 0.4× 132 0.6× 315 2.0× 102 1.9k

Countries citing papers authored by Richard E. Fan

Since Specialization
Citations

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

Fields of papers citing papers by Richard E. Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard E. Fan. 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 Richard E. Fan. The network helps show where Richard E. Fan may publish in the future.

Co-authorship network of co-authors of Richard E. Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Richard E. Fan. A scholar is included among the top collaborators of Richard E. Fan 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 Richard E. Fan. Richard E. Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhou, Steve, Li‐Chun Zhang, Moon Hyung Choi, et al.. (2025). ProMUS ‐ NET : Artificial intelligence detects more prostate cancer than urologists on micro‐ultrasonography. British Journal of Urology. 136(6). 1071–1079.
2.
Li, Cynthia, Indrani Bhattacharya, Sulaiman Vesal, et al.. (2025). ProstAtlasDiff: Prostate cancer detection on MRI using Diffusion Probabilistic Models guided by population spatial cancer atlases. Medical Image Analysis. 101. 103486–103486. 1 indexed citations
3.
Rusu, Mirabela, Sulaiman Vesal, Cynthia Li, et al.. (2025). ProCUSNet: Prostate Cancer Detection on B-mode Transrectal Ultrasound Using Artificial Intelligence for Targeting During Prostate Biopsies. European Urology Oncology. 8(2). 477–485.
4.
Zhang, Lichun, Steve Zhou, Moon Hyung Choi, et al.. (2024). Deep learning for prostate and central gland segmentation on micro-ultrasound images. 30. 5–5. 2 indexed citations
5.
Soerensen, Simon John Christoph, Hriday P. Bhambhvani, Richard E. Fan, et al.. (2024). External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens. British Journal of Urology. 135(1). 133–139. 5 indexed citations
6.
Vesal, Sulaiman, Indrani Bhattacharya, Xinran Li, et al.. (2024). A deep learning framework to assess the feasibility of localizing prostate cancer on b-mode transrectal ultrasound images. 26–26. 1 indexed citations
7.
Shao, Wei, Sulaiman Vesal, Simon John Christoph Soerensen, et al.. (2024). RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate. Computers in Biology and Medicine. 173. 108318–108318. 8 indexed citations
8.
Eminağa, Okyaz, Mahmoud Abbas, Christian A. Kunder, et al.. (2024). Critical evaluation of artificial intelligence as a digital twin of pathologists for prostate cancer pathology. Scientific Reports. 14(1). 5284–5284. 12 indexed citations
9.
Fu, Yunguan, Vasilis Stavrinides, Zachary M. C. Baum, et al.. (2022). Image quality assessment for machine learning tasks using meta-reinforcement learning. Medical Image Analysis. 78. 102427–102427. 28 indexed citations
10.
Fang, Andrew M., Kimberly D. Martin, Richard E. Fan, et al.. (2022). Multi‐institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI‐RADS 3 lesions. Cancer. 128(18). 3287–3296. 21 indexed citations
11.
Vesal, Sulaiman, Indrani Bhattacharya, Shyam Natarajan, et al.. (2022). Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study. Medical Image Analysis. 82. 102620–102620. 22 indexed citations
12.
13.
Bhattacharya, Indrani, Leo C. Chen, Christian A. Kunder, et al.. (2021). Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging. Medical Physics. 48(6). 2960–2972. 41 indexed citations
14.
Wang, Nancy, Steve Zhou, Leo Chen, et al.. (2021). The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer. Urologic Oncology Seminars and Original Investigations. 39(12). 831.e19–831.e27. 14 indexed citations
15.
Awamlh, Bashir Al Hussein Al, Leonard S. Marks, Geoffrey A. Sonn, et al.. (2020). Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions. Urologic Oncology Seminars and Original Investigations. 38(7). 637.e9–637.e15. 18 indexed citations
16.
Shao, Wei, Christian A. Kunder, Richard E. Fan, et al.. (2020). ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate. Medical Image Analysis. 68. 101919–101919. 61 indexed citations
17.
Onofrey, John A., Dana I. Casetti‐Dinescu, Andreas D. Lauritzen, et al.. (2019). Generalizable Multi-Site Training and Testing Of Deep Neural Networks Using Image Normalization. PubMed. 2019. 348–351. 38 indexed citations
18.
Wang, Nancy, Nikola C. Teslovich, Richard E. Fan, et al.. (2019). Applying the PRECISION approach in biopsy naïve and previously negative prostate biopsy patients. Urologic Oncology Seminars and Original Investigations. 37(8). 530.e19–530.e24. 5 indexed citations
19.
Wang, Nancy, Richard E. Fan, John T. Leppert, et al.. (2018). Performance of multiparametric MRI appears better when measured in patients who undergo radical prostatectomy. Research and Reports in Urology. Volume 10. 233–235. 7 indexed citations
20.
Sano, Michael B., Richard E. Fan, & Lei Xing. (2017). Asymmetric Waveforms Decrease Lethal Thresholds in High Frequency Irreversible Electroporation Therapies. Scientific Reports. 7(1). 40747–40747. 51 indexed citations

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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