Vikash Gupta

28 papers receiving 319 citations

Peers

Vikash Gupta
Comparison fields: 5 of 68
  • Health Informatics 53
  • Computational Mathematics 5
  • Radiology, Nuclear Medicine and Imaging 144
  • Rehabilitation 22
  • Nephrology 19
Replace Sebastian Tschauner with:
Sebastian Tschauner Austria
Dana J. Lin United States
Maximilian Patzig Germany
Tom Finck Germany
Kevin Lian Canada
Chieh‐Ju Chao United States
Sarah C. Foreman United States
Viktoria Weixler Germany
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Adil Asghar India
Vikash Gupta relative to Sebastian Tschauner Austria Sebastian Tschauner's profile →
Citations per field
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Citations per year

Countries citing papers authored by Vikash Gupta

Since Specialization
Citations

This map shows the geographic impact of Vikash Gupta'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 Vikash Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikash Gupta more than expected).

Fields of papers citing papers by Vikash Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikash Gupta. 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 Vikash Gupta. The network helps show where Vikash Gupta may publish in the future.

Co-authors

The 25 scholars most cited alongside Vikash Gupta, 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 Vikash Gupta Line = papers co-authored together Vikash Gupta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201953
2 198343
3 201732
4 201927
5 201826
6 201122
7 201621
8 201919
9 202018
10 201713
11 202011
12 20128
13 20136
14 20145
15 20164
16 20082
17 20232
18 20162
19 20162
20 20222

About Vikash Gupta

Vikash Gupta is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery, Biomedical Engineering and Epidemiology, having authored 32 papers that have together received 328 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (5 papers), AI in cancer detection (4 papers), Advanced X-ray and CT Imaging (3 papers), Digital Radiography and Breast Imaging (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Fetal and Pediatric Neurological Disorders (3 papers), Pediatric Hepatobiliary Diseases and Treatments (2 papers) and 3D Shape Modeling and Analysis (2 papers). The work is most often cited by research in Health Informatics (53 citations), Computational Mathematics (5 citations), Radiology, Nuclear Medicine and Imaging (144 citations), Rehabilitation (22 citations) and Nephrology (19 citations). Vikash Gupta has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Paul M. Thompson, Faisal Rashid, Sophia I. Thomopoulos, Barbaros S. Erdal, Mutlu Demirer, Luciano M. Prevedello, Richard D. White, Joseph S. Yu, Thomas O’Donnell and B N Datta. Their work appears in journals such as Journal of Computer Assisted Tomography, Clinical Radiology, Journal of Digital Imaging, Radiology Artificial Intelligence and PLoS ONE.

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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