Kumar Abhinav

37 papers receiving 954 citations

Peers

Kumar Abhinav
Comparison fields: 5 of 93
  • Radiology, Nuclear Medicine and Imaging 393
  • Neurology 254
  • Computer Science Applications 61
  • Genetics 91
  • Endocrinology, Diabetes and Metabolism 131
Replace Michael C. Jin with:
Michael C. Jin United States
Jean‐Michel Lemée France
Fiona Costello Canada
David Netuka Czechia
Laurence Dunn United Kingdom
Walid Ibn Essayed United States
Maurizio Manuguerra Australia
Michael K. McLeod United States
Wei Bian China
Jingyun Wang United States
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Citations per field
00.5×4.6×
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Citations per year

Countries citing papers authored by Kumar Abhinav

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Kumar Abhinav Line = papers co-authored together Kumar Abhinav links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018131
2 2017104
3 201488
4 201573
5 201663
6 201953
7 201544
8 201841
9 201536
10 202031
11 201329
12 202027
13 201424
14 201623
15 201422
16 201721
17 201519
18 201918
19 201116
20 201614

About Kumar Abhinav

Kumar Abhinav is a scholar working on Neurology, Radiology, Nuclear Medicine and Imaging, Surgery, Computer Science Applications and Epidemiology, having authored 38 papers that have together received 972 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (10 papers), Mobile Crowdsensing and Crowdsourcing (8 papers), Meningioma and schwannoma management (7 papers), Head and Neck Surgical Oncology (7 papers), Open Source Software Innovations (5 papers), Pituitary Gland Disorders and Treatments (5 papers), Fetal and Pediatric Neurological Disorders (5 papers) and Moyamoya disease diagnosis and treatment (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (393 citations), Neurology (254 citations), Computer Science Applications (61 citations), Genetics (91 citations) and Endocrinology, Diabetes and Metabolism (131 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, David Fernandes, Sudhir Pathak, Eric W. Wang, Robert M. Friedlander and Alpana Dubey. Their work appears in journals such as Neurosurgery, Operative Neurosurgery, Journal of neurosurgery, Neurotherapeutics and Translational Stroke Research.

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.

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