Ankush Patel
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 10
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- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Anil V. Parwani (10 shared papers)David S. McClintock (3 shared papers)Giovanni Lujan (3 shared papers)Zaibo Li (3 shared papers)Ulysses J. Balis (1 shared paper)Richard J. Chen (1 shared paper)Faisal Mahmood (1 shared paper)Bowen Chen (1 shared paper)
- Journals
- American Journal of Dermatopathology (3 papers)Journal of Pathology Informatics (3 papers)Nature (1 paper)Archives of Pathology & Laboratory Medicine (1 paper)Surgical pathology clinics (1 paper)
- Partner nations
- United StatesSouth KoreaIndia
In The Last Decade
Ankush Patel
16 papers receiving 313 citations
Ankush Patel's Hit Papers
Peers
Comparison fields: 5 of 81
- Health Informatics 72
- Biophysics 35
- Artificial Intelligence 181
- Radiology, Nuclear Medicine and Imaging 120
- Health Information Management 13
Countries citing papers authored by Ankush Patel
This map shows the geographic impact of Ankush Patel'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 Ankush Patel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ankush Patel more than expected).
Fields of papers citing papers by Ankush Patel
This network shows the impact of papers produced by Ankush Patel. 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 Ankush Patel. The network helps show where Ankush Patel may publish in the future.
Co-authors
The 25 scholars most cited alongside Ankush Patel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A multimodal generative AI copilot for human pathology Hit paper breakdown → | 2024 | 156 |
| 2 | 2021 | 67 | |
| 3 | 2023 | 26 | |
| 4 | 2022 | 15 | |
| 5 | 2024 | 15 | |
| 6 | 2023 | 11 | |
| 7 | 2022 | 8 | |
| 8 | 2022 | 7 | |
| 9 | 2022 | 6 | |
| 10 | 2021 | 4 | |
| 11 | 2022 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2022 | 1 | |
| 17 | 2023 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2023 | 0 |
About Ankush Patel
Ankush Patel is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Surgery, Rheumatology and Biophysics, having authored 19 papers that have together received 324 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Cell Image Analysis Techniques (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Urologic and reproductive health conditions (2 papers), Genital Health and Disease (2 papers), Soft tissue tumor case studies (1 paper) and Vascular Tumors and Angiosarcomas (1 paper). The work is most often cited by research in Health Informatics (72 citations), Biophysics (35 citations), Artificial Intelligence (181 citations), Radiology, Nuclear Medicine and Imaging (120 citations) and Health Information Management (13 citations). Ankush Patel has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Anil V. Parwani, David S. McClintock, Giovanni Lujan, Zaibo Li, Ulysses J. Balis, Richard J. Chen, Faisal Mahmood, Bowen Chen, Ivy Liang and Tong Ding. Their work appears in journals such as American Journal of Dermatopathology, Journal of Pathology Informatics, Nature, Archives of Pathology & Laboratory Medicine and Surgical pathology clinics.
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.