Pushpak Pati
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
-
- AI in cancer detection 10
- Neural Networks and Applications 2
- Domain Adaptation and Few-Shot Learning 2
-
- Medical Image Segmentation Techniques 3
- Co-authors
- Maria Gabrani (10 shared papers)Orçun Göksel (7 shared papers)Guillaume Jaume (3 shared papers)Antonio Foncubierta–Rodríguez (1 shared paper)Raúl Catena (2 shared papers)Anna Fomitcheva Khartchenko (2 shared papers)Nadia Brancati (2 shared papers)Florinda Feroce (2 shared papers)
- Journals
- Medical Image Analysis (3 papers)Nature Biomedical Engineering (1 paper)IEEE Transactions on Biomedical Engineering (1 paper)IEEE Transactions on Medical Imaging (1 paper)Complex & Intelligent Systems (1 paper)
- Partner nations
- SwitzerlandUnited StatesIndia
In The Last Decade
Pushpak Pati
20 papers receiving 234 citations
Peers
Comparison fields: 5 of 49
- Health Informatics 9
- Biophysics 33
- Artificial Intelligence 166
- Radiology, Nuclear Medicine and Imaging 101
- Computer Vision and Pattern Recognition 80
Countries citing papers authored by Pushpak Pati
This map shows the geographic impact of Pushpak Pati'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 Pushpak Pati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pushpak Pati more than expected).
Fields of papers citing papers by Pushpak Pati
This network shows the impact of papers produced by Pushpak Pati. 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 Pushpak Pati. The network helps show where Pushpak Pati may publish in the future.
Co-authors
The 25 scholars most cited alongside Pushpak Pati, 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 | 2022 | 65 | |
| 2 | 2019 | 30 | |
| 3 | 2020 | 25 | |
| 4 | 2019 | 24 | |
| 5 | 2024 | 21 | |
| 6 | 2023 | 17 | |
| 7 | 2023 | 10 | |
| 8 | 2016 | 9 | |
| 9 | 2019 | 8 | |
| 10 | 2024 | 6 | |
| 11 | 2023 | 4 | |
| 12 | 2024 | 4 | |
| 13 | Hierarchical Cell-to-Tissue Graph Representations for Breast Cancer Subtyping in Digital Pathology. | 2021 | 3 |
| 14 | 2024 | 3 | |
| 15 | 2019 | 2 | |
| 16 | 2018 | 2 | |
| 17 | âÂÂA REVIEW ON APPLICATION OF CAD AND FEM TECHNOLOGY IN DESIGN OFTAPER DENTAL IMPLANTâ | 2013 | 1 |
| 18 | A Review on FEM Analysis of Mandibular Overdenture Implant | 2013 | 1 |
| 19 | 2024 | 1 | |
| 20 | 2024 | 1 |
About Pushpak Pati
Pushpak Pati is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics and Molecular Biology, having authored 20 papers that have together received 237 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Cell Image Analysis Techniques (5 papers), Medical Image Segmentation Techniques (3 papers), Dental Implant Techniques and Outcomes (2 papers), Neural Networks and Applications (2 papers), Molecular Biology Techniques and Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Health Informatics (9 citations), Biophysics (33 citations), Artificial Intelligence (166 citations), Radiology, Nuclear Medicine and Imaging (101 citations) and Computer Vision and Pattern Recognition (80 citations). Pushpak Pati has collaborated with scholars based in Switzerland, United States and India. Frequent co-authors include Maria Gabrani, Orçun Göksel, Guillaume Jaume, Antonio Foncubierta–Rodríguez, Raúl Catena, Anna Fomitcheva Khartchenko, Nadia Brancati, Florinda Feroce, Gerardo Botti and Maurizio Di Bonito. Their work appears in journals such as Medical Image Analysis, Nature Biomedical Engineering, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Medical Imaging and Complex & Intelligent Systems.
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.