Shankar Thawkar
Impact in
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- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 9
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- Digital Imaging for Blood Diseases 4
- Co-authors
- Law Kumar Singh (13 shared papers)Munish Khanna (13 shared papers)Satish J. Sharma (1 shared paper)Rekha Singh (4 shared papers)Ashish Khanna (1 shared paper)Deepak Gupta (1 shared paper)G. Yamuna (1 shared paper)
- Journals
- Multimedia Tools and Applications (5 papers)International Journal of Imaging Systems and Technology (1 paper)Journal of Applied Biomedicine (1 paper)International journal of innovative computing, information & control (1 paper)Computers in Biology and Medicine (1 paper)
- Partner nations
- India
In The Last Decade
Shankar Thawkar
22 papers receiving 512 citations
Peers
Comparison fields: 5 of 82
- Health Information Management 48
- Radiology, Nuclear Medicine and Imaging 215
- Ophthalmology 67
- Neurology 56
- Artificial Intelligence 237
Countries citing papers authored by Shankar Thawkar
This map shows the geographic impact of Shankar Thawkar'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 Shankar Thawkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shankar Thawkar more than expected).
Fields of papers citing papers by Shankar Thawkar
This network shows the impact of papers produced by Shankar Thawkar. 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 Shankar Thawkar. The network helps show where Shankar Thawkar may publish in the future.
Co-authors
The 7 scholars most cited alongside Shankar Thawkar, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 94 | |
| 2 | 2023 | 53 | |
| 3 | 2023 | 43 | |
| 4 | 2021 | 38 | |
| 5 | 2022 | 37 | |
| 6 | 2021 | 35 | |
| 7 | 2023 | 33 | |
| 8 | 2022 | 31 | |
| 9 | 2018 | 29 | |
| 10 | 2023 | 28 | |
| 11 | 2016 | 23 | |
| 12 | 2023 | 18 | |
| 13 | 2022 | 18 | |
| 14 | 2018 | 15 | |
| 15 | 2018 | 8 | |
| 16 | 2015 | 7 | |
| 17 | 2021 | 5 | |
| 18 | 2021 | 5 | |
| 19 | EFFICIENT APPROACH FOR THE CLASSIFICATION OF MASSES IN DIGITAL MAMMOGRAMS | 2017 | 4 |
| 20 | 2024 | 2 |
About Shankar Thawkar
Shankar Thawkar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Ophthalmology, having authored 22 papers that have together received 529 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Retinal Imaging and Analysis (6 papers), Gene expression and cancer classification (5 papers), Digital Imaging for Blood Diseases (4 papers), Artificial Intelligence in Healthcare (3 papers), Retinal Diseases and Treatments (3 papers), Brain Tumor Detection and Classification (2 papers) and Glaucoma and retinal disorders (2 papers). The work is most often cited by research in Health Information Management (48 citations), Radiology, Nuclear Medicine and Imaging (215 citations), Ophthalmology (67 citations), Neurology (56 citations) and Artificial Intelligence (237 citations). Shankar Thawkar has collaborated with scholars based in India. Frequent co-authors include Law Kumar Singh, Munish Khanna, Satish J. Sharma, Rekha Singh, Ashish Khanna, Deepak Gupta and G. Yamuna. Their work appears in journals such as Multimedia Tools and Applications, International Journal of Imaging Systems and Technology, Journal of Applied Biomedicine, International journal of innovative computing, information & control and Computers in Biology and Medicine.
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.