Jay Patel
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 10
- MRI in cancer diagnosis 5
- Medical Imaging Techniques and Applications 2
- Optical Imaging and Spectroscopy Techniques 2
- Genetics 7
- Glioma Diagnosis and Treatment 7
- Co-authors
- Pallavi Tiwari (4 shared papers)Prateek Prasanna (4 shared papers)Sasan Partovi (4 shared papers)Anant Madabhushi (4 shared papers)Jayashree Kalpathy–Cramer (12 shared papers)Ken Chang (8 shared papers)Katharina Hoebel (9 shared papers)Niha Beig (3 shared papers)
- Journals
- Scientific Reports (2 papers)Radiology (2 papers)Neuro-Oncology (2 papers)Radiology Artificial Intelligence (1 paper)Radiologic Clinics of North America (1 paper)
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Jay Patel
27 papers receiving 719 citations
Peers
Comparison fields: 5 of 81
- Health Informatics 39
- Radiology, Nuclear Medicine and Imaging 447
- Genetics 205
- Neurology 46
- Pulmonary and Respiratory Medicine 179
Countries citing papers authored by Jay Patel
This map shows the geographic impact of Jay 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 Jay Patel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Patel more than expected).
Fields of papers citing papers by Jay Patel
This network shows the impact of papers produced by Jay 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 Jay Patel. The network helps show where Jay Patel may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay 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
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 213 | |
| 2 | 2018 | 114 | |
| 3 | 2019 | 50 | |
| 4 | 2020 | 39 | |
| 5 | 2020 | 37 | |
| 6 | 2018 | 36 | |
| 7 | 2018 | 29 | |
| 8 | 2012 | 26 | |
| 9 | 2022 | 23 | |
| 10 | 2022 | 21 | |
| 11 | 2020 | 20 | |
| 12 | 2019 | 19 | |
| 13 | 2022 | 16 | |
| 14 | 2018 | 14 | |
| 15 | 2020 | 14 | |
| 16 | 2023 | 13 | |
| 17 | 2017 | 10 | |
| 18 | 2021 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2019 | 5 |
About Jay Patel
Jay Patel is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Pulmonary and Respiratory Medicine, Surgery and Artificial Intelligence, having authored 31 papers that have together received 725 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Glioma Diagnosis and Treatment (7 papers), MRI in cancer diagnosis (5 papers), AI in cancer detection (3 papers), Brain Metastases and Treatment (2 papers), Testicular diseases and treatments (2 papers), Medical Imaging Techniques and Applications (2 papers) and Optical Imaging and Spectroscopy Techniques (2 papers). The work is most often cited by research in Health Informatics (39 citations), Radiology, Nuclear Medicine and Imaging (447 citations), Genetics (205 citations), Neurology (46 citations) and Pulmonary and Respiratory Medicine (179 citations). Jay Patel has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Pallavi Tiwari, Prateek Prasanna, Sasan Partovi, Anant Madabhushi, Jayashree Kalpathy–Cramer, Ken Chang, Katharina Hoebel, Niha Beig, Andrew Beers and Vinay Varadan. Their work appears in journals such as Scientific Reports, Radiology, Neuro-Oncology, Radiology Artificial Intelligence and Radiologic Clinics of North America.
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.