Deepak Anand
Impact in
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
- Radiopharmaceutical Chemistry and Applications 2
- COVID-19 diagnosis using AI 1
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- AI in cancer detection 5
- Co-authors
- Amit Sethi (8 shared papers)Walter Wolf (2 shared papers)Neeraj Kumar (2 shared papers)Swapnil Rane (2 shared papers)Peter H. Gann (2 shared papers)James A. Dowell (1 shared paper)Debraj Chakraborty (1 shared paper)Chenyang Wang (1 shared paper)
- Journals
- Cancer Research (1 paper)IEEE Transactions on Industry Applications (1 paper)IEEE Control Systems Letters (1 paper)Journal of Pathology Informatics (1 paper)The Journal of Pathology (1 paper)
- Partner nations
- IndiaUnited StatesCanada
In The Last Decade
Deepak Anand
13 papers receiving 196 citations
Peers
Comparison fields: 5 of 47
- Health Informatics 11
- Radiology, Nuclear Medicine and Imaging 108
- Biophysics 24
- Artificial Intelligence 111
- Computer Vision and Pattern Recognition 36
Countries citing papers authored by Deepak Anand
This map shows the geographic impact of Deepak Anand'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 Deepak Anand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepak Anand more than expected).
Fields of papers citing papers by Deepak Anand
This network shows the impact of papers produced by Deepak Anand. 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 Deepak Anand. The network helps show where Deepak Anand may publish in the future.
Co-authors
The 13 scholars most cited alongside Deepak Anand, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 41 | |
| 2 | 2020 | 34 | |
| 3 | 2021 | 32 | |
| 4 | 2000 | 30 | |
| 5 | 2019 | 22 | |
| 6 | 1992 | 12 | |
| 7 | 2020 | 12 | |
| 8 | 2019 | 6 | |
| 9 | 2022 | 5 | |
| 10 | 2019 | 2 | |
| 11 | 2025 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2017 | 1 | |
| 14 | 2017 | 0 | |
| 15 | 2019 | 0 |
About Deepak Anand
Deepak Anand is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Molecular Biology, Biophysics and Electrical and Electronic Engineering, having authored 15 papers that have together received 199 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Cell Image Analysis Techniques (3 papers), Radiopharmaceutical Chemistry and Applications (2 papers), Analog and Mixed-Signal Circuit Design (1 paper), Electrical Fault Detection and Protection (1 paper), COVID-19 diagnosis using AI (1 paper) and Genetic factors in colorectal cancer (1 paper). The work is most often cited by research in Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (108 citations), Biophysics (24 citations), Artificial Intelligence (111 citations) and Computer Vision and Pattern Recognition (36 citations). Deepak Anand has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Amit Sethi, Walter Wolf, Neeraj Kumar, Swapnil Rane, Peter H. Gann, James A. Dowell, Debraj Chakraborty, Chenyang Wang, Xiaodong Liang and Manpreet Kaur. Their work appears in journals such as Cancer Research, IEEE Transactions on Industry Applications, IEEE Control Systems Letters, Journal of Pathology Informatics and The Journal of Pathology.
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.