Avi Ben-Cohen
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Advanced Image and Video Retrieval Techniques 2
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- Domain Adaptation and Few-Shot Learning 2
- Text and Document Classification Technologies 2
- AI in cancer detection 2
- Co-authors
- Hayit Greenspan (6 shared papers)Eyal Klang (5 shared papers)Michal Marianne Amitai (3 shared papers)Shelly Soffer (1 shared paper)Orit Shimon (1 shared paper)Tal Ridnik (2 shared papers)Emanuel Ben-Baruch (2 shared papers)Asaf Noy (2 shared papers)
- Journals
- ACS Sensors (1 paper)Neurocomputing (1 paper)Academic Radiology (1 paper)Radiology (1 paper)Journal of Medical Imaging (1 paper)
- Partner nations
- IsraelCayman Islands
In The Last Decade
Avi Ben-Cohen
10 papers receiving 595 citations
Avi Ben-Cohen's Hit Papers
Peers
Comparison fields: 5 of 111
- Health Informatics 65
- Radiology, Nuclear Medicine and Imaging 192
- Artificial Intelligence 187
- Computer Vision and Pattern Recognition 96
- Health Information Management 17
Countries citing papers authored by Avi Ben-Cohen
This map shows the geographic impact of Avi Ben-Cohen'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 Avi Ben-Cohen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Avi Ben-Cohen more than expected).
Fields of papers citing papers by Avi Ben-Cohen
This network shows the impact of papers produced by Avi Ben-Cohen. 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 Avi Ben-Cohen. The network helps show where Avi Ben-Cohen may publish in the future.
Co-authors
The 19 scholars most cited alongside Avi Ben-Cohen, 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 | Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide Hit paper breakdown → | 2019 | 379 |
| 2 | 2023 | 52 | |
| 3 | 2017 | 50 | |
| 4 | 2017 | 30 | |
| 5 | 2022 | 28 | |
| 6 | 2018 | 28 | |
| 7 | 2021 | 27 | |
| 8 | 2015 | 8 | |
| 9 | Attention Network Robustification for Person ReID | 2019 | 4 |
| 10 | 2016 | 2 |
About Avi Ben-Cohen
Avi Ben-Cohen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computational Mechanics, having authored 10 papers that have together received 608 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), COVID-19 diagnosis using AI (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Text and Document Classification Technologies (2 papers), AI in cancer detection (2 papers), Nanowire Synthesis and Applications (1 paper) and Advanced X-ray and CT Imaging (1 paper). The work is most often cited by research in Health Informatics (65 citations), Radiology, Nuclear Medicine and Imaging (192 citations), Artificial Intelligence (187 citations), Computer Vision and Pattern Recognition (96 citations) and Health Information Management (17 citations). Avi Ben-Cohen has collaborated with scholars based in Israel and Cayman Islands. Frequent co-authors include Hayit Greenspan, Eyal Klang, Michal Marianne Amitai, Shelly Soffer, Orit Shimon, Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Eli Konen and Itamar Friedman. Their work appears in journals such as ACS Sensors, Neurocomputing, Academic Radiology, Radiology and Journal of Medical Imaging.
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.