Tal Schuster
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- AI in cancer detection
- Topic Modeling
- Natural Language Processing Techniques
Papers in
-
- Topic Modeling 11
- Natural Language Processing Techniques 9
- AI in cancer detection 5
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- Multimodal Machine Learning Applications 2
- Co-authors
- Regina Barzilay (9 shared papers)Adam Yala (5 shared papers)Constance D. Lehman (4 shared papers)Brian N. Dontchos (2 shared papers)Randy C. Miles (1 shared paper)Manisha Bahl (1 shared paper)Kyle Swanson (1 shared paper)Ori Ram (1 shared paper)
- Journals
- Radiology (3 papers)American Journal of Roentgenology (1 paper)JCO Clinical Cancer Informatics (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (1 paper)
- Partner nations
- United StatesIsraelNetherlands
In The Last Decade
Tal Schuster
19 papers receiving 1.0k citations
Tal Schuster's Hit Papers
Peers
Comparison fields: 5 of 102
- Health Informatics 142
- Artificial Intelligence 706
- Radiology, Nuclear Medicine and Imaging 394
- Health Information Management 39
- Pulmonary and Respiratory Medicine 196
Countries citing papers authored by Tal Schuster
This map shows the geographic impact of Tal Schuster'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 Tal Schuster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tal Schuster more than expected).
Fields of papers citing papers by Tal Schuster
This network shows the impact of papers produced by Tal Schuster. 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 Tal Schuster. The network helps show where Tal Schuster may publish in the future.
Co-authors
The 25 scholars most cited alongside Tal Schuster, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction Hit paper breakdown → | 2019 | 462 |
| 2 | 2018 | 196 | |
| 3 | 2019 | 149 | |
| 4 | 2019 | 93 | |
| 5 | 2019 | 28 | |
| 6 | 2020 | 23 | |
| 7 | 2022 | 23 | |
| 8 | 2021 | 22 | |
| 9 | 2022 | 13 | |
| 10 | 2020 | 10 | |
| 11 | 2017 | 9 | |
| 12 | Are We Safe Yet? The Limitations of Distributional Features for Fake News Detection. | 2019 | 6 |
| 13 | 2020 | 4 | |
| 14 | 2024 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2025 | 0 |
About Tal Schuster
Tal Schuster is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology, Radiology, Nuclear Medicine and Imaging and Sociology and Political Science, having authored 21 papers that have together received 1.0k indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (9 papers), AI in cancer detection (5 papers), Global Cancer Incidence and Screening (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Digital Radiography and Breast Imaging (2 papers), Misinformation and Its Impacts (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Health Informatics (142 citations), Artificial Intelligence (706 citations), Radiology, Nuclear Medicine and Imaging (394 citations), Health Information Management (39 citations) and Pulmonary and Respiratory Medicine (196 citations). Tal Schuster has collaborated with scholars based in United States, Israel and Netherlands. Frequent co-authors include Regina Barzilay, Adam Yala, Constance D. Lehman, Brian N. Dontchos, Randy C. Miles, Manisha Bahl, Kyle Swanson, Ori Ram, Amir Globerson and Darsh Shah. Their work appears in journals such as Radiology, American Journal of Roentgenology, JCO Clinical Cancer Informatics, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.