Jay Patel

1.5k citations
31 papers · 725 indexed · h-index 15
Topics
Radiomics and Machine Learning in Medical Imaging (10 papers)Glioma Diagnosis and Treatment (7 papers)MRI in cancer diagnosis (5 papers)
Journals
Journal of Clinical OncologySHILAP Revista de lepidopterologíaNeurology

In The Last Decade

Jay Patel

27 papers receiving 719 citations

Peers

Jay Patel
Comparison fields: 5 of 81
  • Radiology, Nuclear Medicine and Imaging 447
  • Genetics 205
  • Pulmonary and Respiratory Medicine 179
  • Biomedical Engineering 115
  • Surgery 96
Replace Anahita Fathi Kazerooni with:
Anahita Fathi Kazerooni United States
Sebastian Lettmaier Germany
Yangsean Choi South Korea
Jiangfen Wu China
Ryo Kurokawa Japan
Manoj Mannil Switzerland
Sohi Bae South Korea
Natale Quartuccio Italy
Houman Sotoudeh United States
Jinghao Duan China
Jay Patel relative to Anahita Fathi Kazerooni United States Anahita Fathi Kazerooni's profile →
Citations per field
00.5×3.1×
Anahita Fathi Kazerooni · 1×
Citations per year

Countries citing papers authored by Jay Patel

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Jay Patel

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Patel. A scholar is included among the top collaborators of Jay Patel 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 Jay Patel. Jay Patel 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
#WorkIndexed citations
1 0
2 0
3 23
4 21
5 1
6 7
7 7
8 37
9 20
10 5
11 19
12 50
13 0
14 14
15 36
16 114
17 29
18 213
19 26
20 1

About Jay Patel

Jay Patel is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Oral Surgery, 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) and MRI in cancer diagnosis (5 papers). The work is most often cited by research in Health Informatics (39 citations), Radiology, Nuclear Medicine and Imaging (447 citations) and Genetics (205 citations). Jay Patel has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Prateek Prasanna, Sasan Partovi, Pallavi Tiwari, Anant Madabhushi, Jayashree Kalpathy–Cramer, Ken Chang, Katharina Hoebel, Andrew Beers, Niha Beig and Vinay Varadan. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Neurology.

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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