Arko Barman
Impact in
- Health Informatics top 10%
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Video Surveillance and Tracking Methods 7
- Advanced Image and Video Retrieval Techniques 4
- Human Pose and Action Recognition 3
- Medical Image Segmentation Techniques 2
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- Advanced X-ray and CT Imaging 3
- Co-authors
- Shishir K. Shah (5 shared papers)Luca Giancardo (7 shared papers)Sunil A. Sheth (3 shared papers)Songmi Lee (3 shared papers)Sean I. Savitz (3 shared papers)Albert J. Yoo (1 shared paper)Sonja Stieb (3 shared papers)Clifton D. Fuller (3 shared papers)
- Journals
- Medical Physics (2 papers)Journal of Digital Imaging (1 paper)npj Genomic Medicine (1 paper)Frontiers in Neuroscience (1 paper)Journal of Stroke and Cerebrovascular Diseases (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Arko Barman
19 papers receiving 262 citations
Peers
Comparison fields: 5 of 62
- Health Informatics 16
- Radiology, Nuclear Medicine and Imaging 82
- Internal Medicine 13
- Computer Vision and Pattern Recognition 67
- Rehabilitation 21
Countries citing papers authored by Arko Barman
This map shows the geographic impact of Arko Barman'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 Arko Barman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arko Barman more than expected).
Fields of papers citing papers by Arko Barman
This network shows the impact of papers produced by Arko Barman. 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 Arko Barman. The network helps show where Arko Barman may publish in the future.
Co-authors
The 25 scholars most cited alongside Arko Barman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 72 | |
| 2 | 2019 | 32 | |
| 3 | 2021 | 28 | |
| 4 | 2021 | 24 | |
| 5 | 2020 | 24 | |
| 6 | 2017 | 23 | |
| 7 | 2019 | 10 | |
| 8 | 2022 | 9 | |
| 9 | 2022 | 8 | |
| 10 | 2019 | 8 | |
| 11 | 2017 | 7 | |
| 12 | 2018 | 6 | |
| 13 | 2016 | 5 | |
| 14 | 2020 | 4 | |
| 15 | 2022 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2018 | 1 | |
| 20 | 2022 | 0 |
About Arko Barman
Arko Barman is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Epidemiology, having authored 20 papers that have together received 267 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Advanced Image and Video Retrieval Techniques (4 papers), Acute Ischemic Stroke Management (3 papers), Brain Tumor Detection and Classification (3 papers), Advanced X-ray and CT Imaging (3 papers), Human Pose and Action Recognition (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (82 citations), Internal Medicine (13 citations), Computer Vision and Pattern Recognition (67 citations) and Rehabilitation (21 citations). Arko Barman has collaborated with scholars based in United States and China. Frequent co-authors include Shishir K. Shah, Luca Giancardo, Sunil A. Sheth, Songmi Lee, Sean I. Savitz, Albert J. Yoo, Sonja Stieb, Clifton D. Fuller, James C. Grotta and Xiaoqian Jiang. Their work appears in journals such as Medical Physics, Journal of Digital Imaging, npj Genomic Medicine, Frontiers in Neuroscience and Journal of Stroke and Cerebrovascular Diseases.
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.