Debesh Jha
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 16
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- Radiomics and Machine Learning in Medical Imaging 19
- COVID-19 diagnosis using AI 6
- Co-authors
- Pål Halvorsen (12 shared papers)Michael A. Riegler (11 shared papers)Nikhil Kumar Tomar (16 shared papers)Sharib Ali (7 shared papers)Håvard D. Johansen (6 shared papers)Dag Johansen (6 shared papers)Ulaş Bağcı (33 shared papers)Jens Rittscher (3 shared papers)
- Journals
- Scientific Data (3 papers)Alzheimer s & Dementia (2 papers)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Gastrointestinal Endoscopy (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)
- Partner nations
- United StatesNorwayUnited Kingdom
In The Last Decade
Debesh Jha
53 papers receiving 1.6k citations
Debesh Jha's Hit Papers
Peers
Comparison fields: 5 of 103
- Health Informatics 43
- Radiology, Nuclear Medicine and Imaging 616
- Neurology 228
- Computer Vision and Pattern Recognition 594
- Oncology 539
Countries citing papers authored by Debesh Jha
This map shows the geographic impact of Debesh Jha'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 Debesh Jha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debesh Jha more than expected).
Fields of papers citing papers by Debesh Jha
This network shows the impact of papers produced by Debesh Jha. 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 Debesh Jha. The network helps show where Debesh Jha may publish in the future.
Co-authors
The 25 scholars most cited alongside Debesh Jha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy Hit paper breakdown → | 2020 | 279 |
| 2 | Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning Hit paper breakdown → | 2021 | 247 |
| 3 | A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation Hit paper breakdown → | 2021 | 226 |
| 4 | FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation Hit paper breakdown → | 2022 | 174 |
| 5 | 2023 | 135 | |
| 6 | 2022 | 98 | |
| 7 | 2017 | 80 | |
| 8 | 2023 | 73 | |
| 9 | 2022 | 53 | |
| 10 | 2020 | 32 | |
| 11 | 2018 | 29 | |
| 12 | 2023 | 24 | |
| 13 | 2021 | 19 | |
| 14 | 2017 | 19 | |
| 15 | 2022 | 15 | |
| 16 | 2022 | 15 | |
| 17 | 2022 | 14 | |
| 18 | 2022 | 13 | |
| 19 | 2017 | 12 | |
| 20 | 2025 | 12 |
About Debesh Jha
Debesh Jha is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology, Computer Vision and Pattern Recognition and Neurology, having authored 59 papers that have together received 1.7k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (16 papers), Colorectal Cancer Screening and Detection (14 papers), Brain Tumor Detection and Classification (11 papers), COVID-19 diagnosis using AI (6 papers), Advanced Neural Network Applications (4 papers), Gastric Cancer Management and Outcomes (4 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Health Informatics (43 citations), Radiology, Nuclear Medicine and Imaging (616 citations), Neurology (228 citations), Computer Vision and Pattern Recognition (594 citations) and Oncology (539 citations). Debesh Jha has collaborated with scholars based in United States, Norway and United Kingdom. Frequent co-authors include Pål Halvorsen, Michael A. Riegler, Nikhil Kumar Tomar, Sharib Ali, Håvard D. Johansen, Dag Johansen, Ulaş Bağcı, Jens Rittscher, Goo‐Rak Kwon and Thomas de Lange. Their work appears in journals such as Scientific Data, Alzheimer s & Dementia, IEEE Transactions on Neural Networks and Learning Systems, Gastrointestinal Endoscopy and IEEE Journal of Biomedical and Health Informatics.
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.