Som Biswas

2.2k citations
41 papers · 698 indexed · 1 hit paper · h-index 9
Topics
Artificial Intelligence in Healthcare and Education (15 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)COVID-19 diagnosis using AI (5 papers)
Journals
SHILAP Revista de lepidopterologíaRadiologyAmerican Journal of Roentgenology
Partner nations
United StatesIndiaEgypt

In The Last Decade

Som Biswas

38 papers receiving 664 citations

Hit Papers

ChatGPT and the Future of Medical Writing20232026202420252023100200300

Peers

Som Biswas
Comparison fields: 5 of 113
  • Health Informatics 466
  • Artificial Intelligence 245
  • Radiology, Nuclear Medicine and Imaging 237
  • Computer Science Applications 56
  • Public Health, Environmental and Occupational Health 51
Replace Luigi De Angelis with:
Luigi De Angelis Italy
Aidan Gilson United States
Francesco Baglivo Italy
Ketan Paranjape United States
Kay Li Canada
Abhimanyu S. Ahuja United States
Michaela Hardt United States
Sebastian Brodehl Germany
Seth J. Berkowitz United States
Laura Vardoulakis United States
Som Biswas relative to Luigi De Angelis Italy Luigi De Angelis's profile →
Citations per field
00.5×
Luigi De Angelis · 1×
Citations per year

Countries citing papers authored by Som Biswas

Since Specialization
Citations

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

Fields of papers citing papers by Som Biswas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Som Biswas

This figure shows the co-authorship network connecting the top 25 collaborators of Som Biswas. A scholar is included among the top collaborators of Som Biswas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Som Biswas. Som Biswas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 1
3 0
4 4
5 24
6 1
7 28
8 1
9 3
10
ChatGPT and the Future of Medical Writingbreakdown →
384
11 0
12 0
13 1
14 34
15 17
16 82
17 4
18 4
19 5
20 1

About Som Biswas

Som Biswas is a scholar working on Health Informatics, Applied Microbiology and Biotechnology and Radiology, Nuclear Medicine and Imaging, having authored 41 papers that have together received 698 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (15 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Informatics (466 citations), Family Practice (44 citations) and Computer Science Applications (56 citations). Som Biswas has collaborated with scholars based in United States, India and Egypt. Frequent co-authors include Harris L. Cohen, Felipe Kitamura, Paul H. Yi, Rajesh Bhayana, Woo Jin Kim, Judy Wawira Gichoya, Tessa S. Cook, Stephen D. Miller, Neelam Jain and Sherwin S. Chan. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiology and American Journal of Roentgenology.

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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