Ella Barkan
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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- AI in cancer detection 8
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- Radiomics and Machine Learning in Medical Imaging 4
- Co-authors
- Ayelet Akselrod-Ballin (3 shared papers)Michal Rosen‐Zvi (4 shared papers)Sharon Alpert (3 shared papers)Yoel Shoshan (3 shared papers)Sharbell Hashoul (3 shared papers)Michal Guindy (3 shared papers)Adam Spiro (2 shared papers)Varda Shalev (2 shared papers)
- Journals
- Radiology (3 papers)Frontiers in Oncology (1 paper)Computational and Structural Biotechnology Journal (1 paper)The Visual Computer (1 paper)IBM Journal of Research and Development (1 paper)
- Partner nations
- IsraelUnited StatesItaly
In The Last Decade
Ella Barkan
14 papers receiving 268 citations
Peers
Comparison fields: 5 of 56
- Health Informatics 54
- Radiology, Nuclear Medicine and Imaging 178
- Artificial Intelligence 197
- Health Information Management 14
- Computer Vision and Pattern Recognition 57
Countries citing papers authored by Ella Barkan
This map shows the geographic impact of Ella Barkan'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 Ella Barkan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ella Barkan more than expected).
Fields of papers citing papers by Ella Barkan
This network shows the impact of papers produced by Ella Barkan. 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 Ella Barkan. The network helps show where Ella Barkan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ella Barkan, 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 | 2019 | 126 | |
| 2 | 2022 | 40 | |
| 3 | 2015 | 31 | |
| 4 | 2017 | 24 | |
| 5 | 2017 | 12 | |
| 6 | 2022 | 10 | |
| 7 | 2023 | 10 | |
| 8 | 2015 | 8 | |
| 9 | 2009 | 4 | |
| 10 | 2025 | 2 | |
| 11 | 2023 | 2 | |
| 12 | 2011 | 2 | |
| 13 | 1999 | 1 | |
| 14 | 1980 | 1 |
About Ella Barkan
Ella Barkan is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Oncology, having authored 14 papers that have together received 273 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Digital Radiography and Breast Imaging (2 papers), Handwritten Text Recognition Techniques (2 papers), Image Retrieval and Classification Techniques (2 papers), Colorectal Cancer Screening and Detection (2 papers), Global Cancer Incidence and Screening (2 papers) and Surface Roughness and Optical Measurements (1 paper). The work is most often cited by research in Health Informatics (54 citations), Radiology, Nuclear Medicine and Imaging (178 citations), Artificial Intelligence (197 citations), Health Information Management (14 citations) and Computer Vision and Pattern Recognition (57 citations). Ella Barkan has collaborated with scholars based in Israel, United States and Italy. Frequent co-authors include Ayelet Akselrod-Ballin, Michal Rosen‐Zvi, Sharon Alpert, Yoel Shoshan, Sharbell Hashoul, Michal Guindy, Adam Spiro, Varda Shalev, Pavel Kisilev and Michal Chorev. Their work appears in journals such as Radiology, Frontiers in Oncology, Computational and Structural Biotechnology Journal, The Visual Computer and IBM Journal of Research and Development.
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.