Igor Odintsov
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- AI in cancer detection
Papers in
-
- Sarcoma Diagnosis and Treatment 4
- Lung Cancer Treatments and Mutations 2
- Oncology 8
- Vascular Tumors and Angiosarcomas 2
- Co-authors
- Ivy Liang (1 shared paper)Richard J. Chen (1 shared paper)Bowen Chen (1 shared paper)Tong Ding (1 shared paper)Drew F. K. Williamson (1 shared paper)Long P. Le (1 shared paper)Guillaume Jaume (1 shared paper)Andrew Zhang (1 shared paper)
- Journals
- The American Journal of Surgical Pathology (7 papers)Molecular Cancer Therapeutics (1 paper)Nature Medicine (1 paper)Laboratory Investigation (1 paper)Modern Pathology (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Igor Odintsov
11 papers receiving 337 citations
Igor Odintsov's Hit Papers
Peers
Comparison fields: 5 of 46
- Health Informatics 28
- Artificial Intelligence 171
- Biophysics 26
- Radiology, Nuclear Medicine and Imaging 93
- Computer Vision and Pattern Recognition 64
Countries citing papers authored by Igor Odintsov
This map shows the geographic impact of Igor Odintsov'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 Igor Odintsov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor Odintsov more than expected).
Fields of papers citing papers by Igor Odintsov
This network shows the impact of papers produced by Igor Odintsov. 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 Igor Odintsov. The network helps show where Igor Odintsov may publish in the future.
Co-authors
The 25 scholars most cited alongside Igor Odintsov, 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 | A visual-language foundation model for computational pathology Hit paper breakdown → | 2024 | 304 |
| 2 | 2023 | 10 | |
| 3 | 2024 | 8 | |
| 4 | 2022 | 8 | |
| 5 | 2024 | 7 | |
| 6 | 2025 | 4 | |
| 7 | 2025 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 1 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 1 | |
| 12 | 2023 | 0 | |
| 13 | 2023 | 0 | |
| 14 | 2025 | 0 | |
| 15 | 2025 | 0 |
About Igor Odintsov
Igor Odintsov is a scholar working on Pulmonary and Respiratory Medicine, Oncology, Molecular Biology, Rheumatology and Surgery, having authored 15 papers that have together received 348 indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (4 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers), Bone Tumor Diagnosis and Treatments (2 papers), Oral and Maxillofacial Pathology (2 papers), Neuroendocrine Tumor Research Advances (2 papers), Soft tissue tumor case studies (2 papers), Vascular Tumors and Angiosarcomas (2 papers) and Lung Cancer Treatments and Mutations (2 papers). The work is most often cited by research in Health Informatics (28 citations), Artificial Intelligence (171 citations), Biophysics (26 citations), Radiology, Nuclear Medicine and Imaging (93 citations) and Computer Vision and Pattern Recognition (64 citations). Igor Odintsov has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Ivy Liang, Richard J. Chen, Bowen Chen, Tong Ding, Drew F. K. Williamson, Long P. Le, Guillaume Jaume, Andrew Zhang, Anil V. Parwani and Georg K. Gerber. Their work appears in journals such as The American Journal of Surgical Pathology, Molecular Cancer Therapeutics, Nature Medicine, Laboratory Investigation and Modern Pathology.
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.