Kumar Abhinav
Impact in
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- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Neurology top 10%
Papers in
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- Mobile Crowdsensing and Crowdsourcing 8
- Open Source Software Innovations 5
- Co-authors
- Fang‐Cheng Yeh (9 shared papers)Juan C. Fernandez‐Miranda (13 shared papers)Paul A. Gardner (7 shared papers)Sandip S. Panesar (5 shared papers)Juan C. Fernandez‐Miranda (5 shared papers)Sudhir Pathak (4 shared papers)David Fernandes (2 shared papers)Eric W. Wang (4 shared papers)
- Journals
- Neurosurgery (4 papers)Journal of neurosurgery (3 papers)Operative Neurosurgery (3 papers)Neurotherapeutics (2 papers)Frontiers in Human Neuroscience (1 paper)
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Kumar Abhinav
38 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 89
- Radiology, Nuclear Medicine and Imaging 322
- Neurology 168
- Computer Science Applications 66
- Endocrinology, Diabetes and Metabolism 101
- Genetics 60
Countries citing papers authored by Kumar Abhinav
This map shows the geographic impact of Kumar Abhinav'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 Kumar Abhinav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Abhinav more than expected).
Fields of papers citing papers by Kumar Abhinav
This network shows the impact of papers produced by Kumar Abhinav. 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 Kumar Abhinav. The network helps show where Kumar Abhinav may publish in the future.
Co-authors
The 25 scholars most cited alongside Kumar Abhinav, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 141 | |
| 2 | 2017 | 111 | |
| 3 | 2014 | 95 | |
| 4 | 2015 | 75 | |
| 5 | 2016 | 68 | |
| 6 | 2019 | 55 | |
| 7 | 2015 | 45 | |
| 8 | 2018 | 44 | |
| 9 | 2020 | 40 | |
| 10 | 2015 | 39 | |
| 11 | 2013 | 31 | |
| 12 | 2020 | 30 | |
| 13 | 2014 | 24 | |
| 14 | 2016 | 24 | |
| 15 | 2014 | 22 | |
| 16 | 2015 | 22 | |
| 17 | 2017 | 22 | |
| 18 | 2019 | 19 | |
| 19 | 2011 | 18 | |
| 20 | 2017 | 16 |
About Kumar Abhinav
Kumar Abhinav is a scholar working on Neurology, Computer Science Applications, Surgery, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 39 papers that have together received 1.0k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (8 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Head and Neck Surgical Oncology (5 papers), Open Source Software Innovations (5 papers), Moyamoya disease diagnosis and treatment (3 papers), Fetal and Pediatric Neurological Disorders (3 papers), Recommender Systems and Techniques (3 papers) and Meningioma and schwannoma management (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (322 citations), Neurology (168 citations), Computer Science Applications (66 citations), Endocrinology, Diabetes and Metabolism (101 citations) and Genetics (60 citations). Kumar Abhinav has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Fang‐Cheng Yeh, Juan C. Fernandez‐Miranda, Paul A. Gardner, Sandip S. Panesar, Juan C. Fernandez‐Miranda, Sudhir Pathak, David Fernandes, Eric W. Wang, Alpana Dubey and Robert M. Friedlander. Their work appears in journals such as Neurosurgery, Journal of neurosurgery, Operative Neurosurgery, Neurotherapeutics and Frontiers in Human Neuroscience.
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.