Vivek Vaidya
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence
- Pulmonary and Respiratory Medicine
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Co-authors
- Junjie ShanXiaojie HuangHariharan RavishankarNitin SinghalVarun JampaniJayanthi SivaswamyFei ZhaoChuyang Ye
- Topics
- Medical Image Segmentation Techniques (5 papers)AI in cancer detection (5 papers)Image Retrieval and Classification Techniques (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsComputer Vision and Pattern Recognition
- Journals
- PubMedCERN Document Server (European Organization for Nuclear Research)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Vivek Vaidya
14 papers receiving 207 citations
Peers
Comparison fields: 5 of 55
- Radiology, Nuclear Medicine and Imaging 144
- Artificial Intelligence 83
- Pulmonary and Respiratory Medicine 74
- Computer Vision and Pattern Recognition 60
- Biomedical Engineering 19
Countries citing papers authored by Vivek Vaidya
This map shows the geographic impact of Vivek Vaidya'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 Vivek Vaidya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivek Vaidya more than expected).
Fields of papers citing papers by Vivek Vaidya
This network shows the impact of papers produced by Vivek Vaidya. 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 Vivek Vaidya. The network helps show where Vivek Vaidya may publish in the future.
Co-authorship network of co-authors of Vivek Vaidya
This figure shows the co-authorship network connecting the top 25 collaborators of Vivek Vaidya. A scholar is included among the top collaborators of Vivek Vaidya 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 Vivek Vaidya. Vivek Vaidya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | Data Driven: Harnessing Data and AI to Reinvent Customer Engagement | 4 |
| 7 | 119 | |
| 8 | 37 | |
| 9 | 1 | |
| 10 | 12 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 29 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 2 |
About Vivek Vaidya
Vivek Vaidya is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Health Information Management, having authored 18 papers that have together received 219 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), AI in cancer detection (5 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (144 citations), Health Informatics (7 citations) and Computer Vision and Pattern Recognition (60 citations). Vivek Vaidya has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Junjie Shan, Xiaojie Huang, Hariharan Ravishankar, Nitin Singhal, Varun Jampani, Jayanthi Sivaswamy, Fei Zhao, Chuyang Ye, Soma Biswas and V. Seshagiri Rao. Their work appears in journals such as PubMed, CERN Document Server (European Organization for Nuclear Research) and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.