Jayashree Kalpathy-Cramer
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Neurology
- Computer Vision and Pattern Recognition
- Health Informatics
- Co-authors
- Christopher P. BridgeElizabeth R. GerstnerEric YangMatthew LiMin LangFrancis DengAmbrose J. HuangMarc D. Succi
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)COVID-19 diagnosis using AI (4 papers)Artificial Intelligence in Healthcare and Education (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaOphthalmologyBritish Journal of Radiology
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jayashree Kalpathy-Cramer
6 papers receiving 40 citations
Hit Papers
Peers
Comparison fields: 5 of 27
- Artificial Intelligence 15
- Radiology, Nuclear Medicine and Imaging 15
- Neurology 14
- Computer Vision and Pattern Recognition 10
- Health Informatics 5
Countries citing papers authored by Jayashree Kalpathy-Cramer
This map shows the geographic impact of Jayashree Kalpathy-Cramer'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 Jayashree Kalpathy-Cramer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jayashree Kalpathy-Cramer more than expected).
Fields of papers citing papers by Jayashree Kalpathy-Cramer
This network shows the impact of papers produced by Jayashree Kalpathy-Cramer. 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 Jayashree Kalpathy-Cramer. The network helps show where Jayashree Kalpathy-Cramer may publish in the future.
Co-authorship network of co-authors of Jayashree Kalpathy-Cramer
This figure shows the co-authorship network connecting the top 25 collaborators of Jayashree Kalpathy-Cramer. A scholar is included among the top collaborators of Jayashree Kalpathy-Cramer 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 Jayashree Kalpathy-Cramer. Jayashree Kalpathy-Cramer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A review of deep learning for brain tumor analysis in MRIbreakdown → | 16 |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 14 |
About Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 10 papers that have together received 41 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (4 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (5 citations), Neurology (14 citations) and Radiology, Nuclear Medicine and Imaging (15 citations). Jayashree Kalpathy-Cramer has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Christopher P. Bridge, Elizabeth R. Gerstner, Eric Yang, Matthew Li, Min Lang, Francis Deng, Ambrose J. Huang, Marc D. Succi, Berkman Sahiner and Weijie Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, Ophthalmology and British Journal of 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.