Jay Patel
Impact in
- Health Informatics top 5%
- Genetics top 5%
- Glioma Diagnosis and Treatment
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 10
- MRI in cancer diagnosis 3
- Medical Imaging Techniques and Applications 2
- Genetics 8
- Glioma Diagnosis and Treatment 8
- Co-authors
- Sasan Partovi (4 shared papers)Pallavi Tiwari (4 shared papers)Prateek Prasanna (4 shared papers)Anant Madabhushi (4 shared papers)Jayashree Kalpathy–Cramer (12 shared papers)Ken Chang (9 shared papers)Katharina Hoebel (9 shared papers)Niha Beig (3 shared papers)
- Journals
- Scientific Reports (2 papers)Neuro-Oncology (2 papers)IEEE Transactions on Medical Imaging (1 paper)Journal of Thoracic and Cardiovascular Surgery (1 paper)Radiology (1 paper)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Jay Patel
29 papers receiving 767 citations
Peers
Comparison fields: 5 of 80
- Health Informatics 30
- Genetics 183
- Radiology, Nuclear Medicine and Imaging 323
- Neurology 51
- Neurology 66
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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 221 | |
| 2 | 2018 | 121 | |
| 3 | 2019 | 52 | |
| 4 | 2018 | 44 | |
| 5 | 2020 | 39 | |
| 6 | 2020 | 39 | |
| 7 | 2018 | 32 | |
| 8 | 2012 | 30 | |
| 9 | 2022 | 27 | |
| 10 | 2020 | 24 | |
| 11 | 2019 | 21 | |
| 12 | 2022 | 18 | |
| 13 | 2023 | 18 | |
| 14 | 2020 | 15 | |
| 15 | 2018 | 14 | |
| 16 | 2022 | 11 | |
| 17 | 2017 | 11 | |
| 18 | 2021 | 8 | |
| 19 | 2021 | 7 | |
| 20 | 2019 | 5 |
About Jay Patel
Jay Patel is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Surgery, Neurology and Pulmonary and Respiratory Medicine, having authored 33 papers that have together received 774 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Glioma Diagnosis and Treatment (8 papers), MRI in cancer diagnosis (3 papers), Brain Tumor Detection and Classification (2 papers), Medical Imaging Techniques and Applications (2 papers), Intracranial Aneurysms: Treatment and Complications (2 papers), Dental Radiography and Imaging (2 papers) and Digital Imaging in Medicine (2 papers). The work is most often cited by research in Health Informatics (30 citations), Genetics (183 citations), Radiology, Nuclear Medicine and Imaging (323 citations), Neurology (51 citations) and Neurology (66 citations). Jay Patel has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Sasan Partovi, Pallavi Tiwari, Prateek Prasanna, 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, Neuro-Oncology, IEEE Transactions on Medical Imaging, Journal of Thoracic and Cardiovascular Surgery and Radiology.
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.