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 15
- Natural Language Processing Techniques 12
- AI in cancer detection 5
- Text Readability and Simplification 2
- Adversarial Robustness in Machine Learning 2
- Co-authors
- Regina Barzilay (12 shared papers)Adam Yala (5 shared papers)Constance Dobbins Lehman (4 shared papers)Brian Nicholas Dontchos (2 shared papers)Randy C. Miles (1 shared paper)Ori Ram (1 shared paper)Amir Globerson (1 shared paper)Manisha Bahl (1 shared paper)
- Journals
- Radiology (3 papers)JCO Clinical Cancer Informatics (1 paper)American Journal of Roentgenology (1 paper)Computational Linguistics (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Tal Schuster
23 papers receiving 1.2k citations
Tal Schuster's Hit Papers
Peers
Comparison fields: 5 of 109
- Health Informatics 156
- Artificial Intelligence 816
- Radiology, Nuclear Medicine and Imaging 426
- Health Information Management 45
- Pulmonary and Respiratory Medicine 216
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 26 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 | 527 |
| 2 | 2018 | 212 | |
| 3 | 2019 | 163 | |
| 4 | 2019 | 121 | |
| 5 | 2019 | 30 | |
| 6 | 2022 | 27 | |
| 7 | 2020 | 25 | |
| 8 | 2021 | 22 | |
| 9 | 2022 | 14 | |
| 10 | 2017 | 12 | |
| 11 | 2020 | 11 | |
| 12 | 2020 | 8 | |
| 13 | 2022 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2024 | 4 | |
| 17 | 2019 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2021 | 3 | |
| 20 | 2023 | 2 |
About Tal Schuster
Tal Schuster is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Oncology and Information Systems, having authored 26 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (12 papers), AI in cancer detection (5 papers), Misinformation and Its Impacts (3 papers), Global Cancer Incidence and Screening (3 papers), Digital Radiography and Breast Imaging (2 papers), Text Readability and Simplification (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Health Informatics (156 citations), Artificial Intelligence (816 citations), Radiology, Nuclear Medicine and Imaging (426 citations), Health Information Management (45 citations) and Pulmonary and Respiratory Medicine (216 citations). Tal Schuster has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Regina Barzilay, Adam Yala, Constance Dobbins Lehman, Brian Nicholas Dontchos, Randy C. Miles, Ori Ram, Amir Globerson, Manisha Bahl, Kyle Swanson and Darsh Shah. Their work appears in journals such as Radiology, JCO Clinical Cancer Informatics, American Journal of Roentgenology, Computational Linguistics and arXiv (Cornell University).
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.