Tripti Swarnkar

65 papers receiving 555 citations

Peers

Tripti Swarnkar
Comparison fields: 5 of 101
  • Health Informatics 14
  • Artificial Intelligence 278
  • Neurology 64
  • Radiology, Nuclear Medicine and Imaging 176
  • Health Information Management 35
Replace Muhammad Umar Nasir with:
Muhammad Umar Nasir Pakistan
Dev Kumar Das India
Law Kumar Singh India
Munish Khanna India
Chetna Kaushal India
Md. Rezwanul Haque Bangladesh
Mahmudul Hasan United States
Rekha Singh India
Tahira Nazir Pakistan
Eugenio Vocaturo Italy
Tripti Swarnkar relative to Muhammad Umar Nasir Pakistan Muhammad Umar Nasir's profile →
Citations per field
00.5×3.4×
Muhammad Umar Nasir · 1×
Citations per year

Countries citing papers authored by Tripti Swarnkar

Since Specialization
Citations

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

Fields of papers citing papers by Tripti Swarnkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202142
2 202042
3 201740
4 202240
5 202040
6 202335
7 201517
8 202116
9 202016
10 201016
11 201815
12 201814
13 201813
14 201712
15 201912
16 201511
17 202410
18 202110
19 202310
20 202010

About Tripti Swarnkar

Tripti Swarnkar is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Media Technology, having authored 74 papers that have together received 588 indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Gene expression and cancer classification (15 papers), Digital Imaging for Blood Diseases (10 papers), Machine Learning in Bioinformatics (10 papers), COVID-19 diagnosis using AI (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Bioinformatics and Genomic Networks (7 papers) and Artificial Intelligence in Healthcare (6 papers). The work is most often cited by research in Health Informatics (14 citations), Artificial Intelligence (278 citations), Neurology (64 citations), Radiology, Nuclear Medicine and Imaging (176 citations) and Health Information Management (35 citations). Tripti Swarnkar has collaborated with scholars based in India, United States and Brazil. Frequent co-authors include Santisudha Panigrahi, Subhashree Mohapatra, Manohar Mishra, Girish Kumar Pati, Priyadarshini Adyasha Pattanaik, Debasish Swapnesh Kumar Nayak, Alok Kumar Jagadev, Pravat Kumar Rout, Ruchi Bhuyan and Pabitra Mitra. Their work appears in journals such as Journal of King Saud University - Computer and Information Sciences, Heliyon, Gene Expression, Mathematical Biosciences & Engineering and Frontiers in Bioscience-Landmark.

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.

Explore authors with similar magnitude of impact