Pushpak Pati
Impact in
- Artificial Intelligence top 10%
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
Papers in
-
- AI in cancer detection 10
- Domain Adaptation and Few-Shot Learning 2
-
- Medical Image Segmentation Techniques 3
- Digital Imaging for Blood Diseases 2
- Co-authors
- Maria Gabrani (10 shared papers)Orçun Göksel (7 shared papers)Guillaume Jaume (3 shared papers)Antonio Foncubierta–Rodríguez (1 shared paper)Giuseppe De Pietro (2 shared papers)Maria Frucci (2 shared papers)Daniel Riccio (2 shared papers)Gerardo Botti (2 shared papers)
- Journals
- Medical Image Analysis (3 papers)Database (1 paper)Briefings in Bioinformatics (1 paper)Frontiers in Medicine (1 paper)Nature Biomedical Engineering (1 paper)
- Partner nations
- SwitzerlandUnited StatesSweden
In The Last Decade
Pushpak Pati
19 papers receiving 263 citations
Peers
Comparison fields: 5 of 52
- Health Informatics 8
- Artificial Intelligence 176
- Biophysics 30
- Radiology, Nuclear Medicine and Imaging 95
- Computer Vision and Pattern Recognition 78
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 | 75 | |
| 2 | 2024 | 31 | |
| 3 | 2019 | 30 | |
| 4 | 2020 | 26 | |
| 5 | 2019 | 26 | |
| 6 | 2023 | 17 | |
| 7 | 2023 | 13 | |
| 8 | 2016 | 9 | |
| 9 | 2019 | 8 | |
| 10 | 2024 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2024 | 4 | |
| 14 | Hierarchical Cell-to-Tissue Graph Representations for Breast Cancer Subtyping in Digital Pathology. | 2021 | 3 |
| 15 | 2024 | 2 | |
| 16 | 2018 | 2 | |
| 17 | 2019 | 2 | |
| 18 | âÂÂA REVIEW ON APPLICATION OF CAD AND FEM TECHNOLOGY IN DESIGN OFTAPER DENTAL IMPLANTâ | 2013 | 1 |
| 19 | 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 19 papers that have together received 267 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), Digital Imaging for Blood Diseases (2 papers), Colorectal Cancer Screening and Detection (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 (8 citations), Artificial Intelligence (176 citations), Biophysics (30 citations), Radiology, Nuclear Medicine and Imaging (95 citations) and Computer Vision and Pattern Recognition (78 citations). Pushpak Pati has collaborated with scholars based in Switzerland, United States and Sweden. Frequent co-authors include Maria Gabrani, Orçun Göksel, Guillaume Jaume, Antonio Foncubierta–Rodríguez, Giuseppe De Pietro, Maria Frucci, Daniel Riccio, Gerardo Botti, Nadia Brancati and Raúl Catena. Their work appears in journals such as Medical Image Analysis, Database, Briefings in Bioinformatics, Frontiers in Medicine and Nature Biomedical Engineering.
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.