Abhinav Kumar
Impact in
- Microbiology top 2%
- Antimicrobial Peptides and Activities
- Artificial Intelligence top 5%
- AI in cancer detection
Papers in
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- Machine Learning in Bioinformatics 7
- vaccines and immunoinformatics approaches 7
- Biochemical and Structural Characterization 4
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- AI in cancer detection 8
- Co-authors
- Sanjay Kumar Singh (19 shared papers)Sonal Saxena (15 shared papers)Sameer Shrivastava (13 shared papers)Amit Kumar Singh (11 shared papers)Rishav Singh (5 shared papers)Ritesh Sharma (6 shared papers)Vandana Bharti (5 shared papers)Raj Kumar Singh (4 shared papers)
- Journals
- Briefings in Bioinformatics (5 papers)IEEE Journal of Biomedical and Health Informatics (5 papers)IEEE Transactions on Industrial Informatics (2 papers)IEEE Transactions on Fuzzy Systems (2 papers)Cellular Immunology (1 paper)
- Partner nations
- IndiaRussiaSaudi Arabia
In The Last Decade
Abhinav Kumar
35 papers receiving 978 citations
Peers
Comparison fields: 5 of 108
- Microbiology 218
- Artificial Intelligence 384
- Radiology, Nuclear Medicine and Imaging 240
- Health Informatics 14
- Neurology 83
Countries citing papers authored by Abhinav Kumar
This map shows the geographic impact of Abhinav Kumar'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 Abhinav Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhinav Kumar more than expected).
Fields of papers citing papers by Abhinav Kumar
This network shows the impact of papers produced by Abhinav Kumar. 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 Abhinav Kumar. The network helps show where Abhinav Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Abhinav Kumar, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 187 | |
| 2 | 2021 | 128 | |
| 3 | 2020 | 102 | |
| 4 | 2021 | 92 | |
| 5 | 2021 | 56 | |
| 6 | 2021 | 52 | |
| 7 | 2021 | 46 | |
| 8 | 2021 | 43 | |
| 9 | 2021 | 39 | |
| 10 | 2020 | 34 | |
| 11 | 2021 | 29 | |
| 12 | 2022 | 26 | |
| 13 | 2019 | 23 | |
| 14 | 2018 | 19 | |
| 15 | 2023 | 17 | |
| 16 | 2021 | 13 | |
| 17 | 2022 | 12 | |
| 18 | 2023 | 11 | |
| 19 | 2023 | 10 | |
| 20 | 2023 | 10 |
About Abhinav Kumar
Abhinav Kumar is a scholar working on Molecular Biology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Microbiology and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 1.0k indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Machine Learning in Bioinformatics (7 papers), Antimicrobial Peptides and Activities (7 papers), vaccines and immunoinformatics approaches (7 papers), COVID-19 diagnosis using AI (6 papers), Biochemical and Structural Characterization (4 papers), Complex Network Analysis Techniques (4 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Microbiology (218 citations), Artificial Intelligence (384 citations), Radiology, Nuclear Medicine and Imaging (240 citations), Health Informatics (14 citations) and Neurology (83 citations). Abhinav Kumar has collaborated with scholars based in India, Russia and Saudi Arabia. Frequent co-authors include Sanjay Kumar Singh, Sonal Saxena, Sameer Shrivastava, Amit Kumar Singh, Rishav Singh, Ritesh Sharma, Vandana Bharti, Raj Kumar Singh, K. Lakshmanan and Raj Kumar Singh. Their work appears in journals such as Briefings in Bioinformatics, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Fuzzy Systems and Cellular Immunology.
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.