Ashwin Verma

29 papers receiving 797 citations

Ashwin Verma's Hit Papers

Explainable AI for Healthcare 5.0: Opportunities and Challenges 2022 · 250 citations
2500+1+2Years since publication50100150200250

Peers

Ashwin Verma
Comparison fields: 5 of 113
  • Health Informatics 106
  • Health Information Management 40
  • Information Systems 191
  • Artificial Intelligence 255
  • Industrial and Manufacturing Engineering 75
Replace Zenun Kastrati with:
Zenun Kastrati Sweden
Deepti Saraswat India
Rodolfo Stoffel Antunes Brazil
Francesca Fallucchi Italy
Mohamed Abdulnabi Malaysia
Angela Locoro Italy
Sara Montagna Italy
M.A. Chyad Malaysia
Sher Muhammad Daudpota Pakistan
Ashwin Verma relative to Zenun Kastrati Sweden Zenun Kastrati's profile →
Citations per field
00.5×2.8×
Zenun Kastrati · 1×
Citations per year

Countries citing papers authored by Ashwin Verma

Since Specialization
Citations

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

Fields of papers citing papers by Ashwin Verma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Explainable AI for Healthcare 5.0: Opportunities and Challenges
Hit paper breakdown →
2022250
2 202293
3 202270
4 202362
5 202149
6 202236
7 202428
8 199927
9 202122
10 199920
11 202220
12 202319
13 202215
14 202215
15 202114
16 202412
17 200711
18 202210
19 202210
20 20218

About Ashwin Verma

Ashwin Verma is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Electrical and Electronic Engineering and Radiology, Nuclear Medicine and Imaging, having authored 29 papers that have together received 821 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (9 papers), IoT and Edge/Fog Computing (8 papers), UAV Applications and Optimization (4 papers), COVID-19 diagnosis using AI (4 papers), Privacy-Preserving Technologies in Data (4 papers), Machine Learning in Healthcare (3 papers), Liver Diseases and Immunity (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). The work is most often cited by research in Health Informatics (106 citations), Health Information Management (40 citations), Information Systems (191 citations), Artificial Intelligence (255 citations) and Industrial and Manufacturing Engineering (75 citations). Ashwin Verma has collaborated with scholars based in India, United Kingdom and South Africa. Frequent co-authors include Pronaya Bhattacharya, Sudeep Tanwar, Ravi Sharma, Deepti Saraswat, Gulshan Sharma, Pitshou N. Bokoro, Vivek Kumar Prasad, Neeraj Kumar, Mohd Zuhair and Bharat Bhushan. Their work appears in journals such as IEEE Access, European Journal of Gastroenterology & Hepatology, Journal of Information Security and Applications, Computer Standards & Interfaces and Journal of Hepatology.

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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