Saeed Amal
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- AI in cancer detection 6
- Advanced Graph Neural Networks 3
- Semantic Web and Ontologies 2
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- Data Visualization and Analytics 3
- Co-authors
- Elsie Ross (5 shared papers)Jesutofunmi A. Omiye (2 shared papers)Anne Breggia (5 shared papers)Einat Minkov (5 shared papers)Tsvi Kuflik (4 shared papers)Peter Brusilovsky (4 shared papers)Vy T. Ho (2 shared papers)Steven M. Asch (2 shared papers)
- Journals
- Cancers (2 papers)Scientific Reports (1 paper)Biomedicines (1 paper)Frontiers in Cardiovascular Medicine (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Saeed Amal
17 papers receiving 206 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 28
- Health Information Management 39
- Artificial Intelligence 91
- Radiology, Nuclear Medicine and Imaging 59
- Family Practice 4
Countries citing papers authored by Saeed Amal
This map shows the geographic impact of Saeed Amal'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 Saeed Amal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saeed Amal more than expected).
Fields of papers citing papers by Saeed Amal
This network shows the impact of papers produced by Saeed Amal. 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 Saeed Amal. The network helps show where Saeed Amal may publish in the future.
Co-authors
The 23 scholars most cited alongside Saeed Amal, 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 | 2022 | 84 | |
| 2 | 2024 | 20 | |
| 3 | 2024 | 19 | |
| 4 | 2022 | 18 | |
| 5 | 2019 | 14 | |
| 6 | 2023 | 13 | |
| 7 | 2024 | 11 | |
| 8 | 2023 | 11 | |
| 9 | 2024 | 6 | |
| 10 | 2017 | 6 | |
| 11 | 2023 | 4 | |
| 12 | 2025 | 3 | |
| 13 | 2020 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2019 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2024 | 1 |
About Saeed Amal
Saeed Amal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 217 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Peripheral Artery Disease Management (4 papers), Clinical practice guidelines implementation (3 papers), Advanced Graph Neural Networks (3 papers), Data Visualization and Analytics (3 papers), Recommender Systems and Techniques (3 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Health Informatics (28 citations), Health Information Management (39 citations), Artificial Intelligence (91 citations), Radiology, Nuclear Medicine and Imaging (59 citations) and Family Practice (4 citations). Saeed Amal has collaborated with scholars based in United States and Israel. Frequent co-authors include Elsie Ross, Jesutofunmi A. Omiye, Anne Breggia, Einat Minkov, Tsvi Kuflik, Peter Brusilovsky, Vy T. Ho, Steven M. Asch, Stephen Ryan and Chun-Hua Tsai. Their work appears in journals such as Cancers, Scientific Reports, Biomedicines, Frontiers in Cardiovascular Medicine and Expert Systems with Applications.
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.