Shaker El–Sappagh
- Health Informatics top 0.1%
- Health Information Management top 0.05%
- Artificial Intelligence in Healthcare 35
- Artificial Intelligence top 0.5%
- Machine Learning in Healthcare 29
- Semantic Web and Ontologies 23
- AI in cancer detection 12
- Anomaly Detection Techniques and Applications 9
- Neurology top 2%
- Brain Tumor Detection and Classification 11
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- COVID-19 diagnosis using AI 13
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- Biomedical Text Mining and Ontologies 24
- Co-authors
- Farman AliKyung Sup KwakTamer AbuhmedS. M. Riazul IslamJosé M. AlonsoAmjad AliDaehan KwakMohammed Elmogy
- Journals
- IEEE Access (16 papers)Electronics (7 papers)Computers, materials & continua/Computers, materials & continua (Print) (7 papers)
- Partner nations
- EgyptSouth KoreaSaudi Arabia
In The Last Decade
Shaker El–Sappagh
141 papers receiving 5.1k citations
Hit Papers
Peers
Comparison fields: 5 of 197
- Health Informatics 403
- Health Information Management 1.0k
- Artificial Intelligence 2.3k
- Neurology 374
- Radiology, Nuclear Medicine and Imaging 815
Countries citing papers authored by Shaker El–Sappagh
This map shows the geographic impact of Shaker El–Sappagh'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 Shaker El–Sappagh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaker El–Sappagh more than expected).
Fields of papers citing papers by Shaker El–Sappagh
This network shows the impact of papers produced by Shaker El–Sappagh. 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 Shaker El–Sappagh. The network helps show where Shaker El–Sappagh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shaker El–Sappagh, 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 | 2025 | 3 | |
| 2 | 2025 | 4 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 15 | |
| 6 | 2024 | 3 | |
| 7 | 2023 | 39 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 29 | |
| 10 | Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligencebreakdown → | 2023 | 687 |
| 11 | 2023 | 4 | |
| 12 | 2023 | 23 | |
| 13 | 2023 | 13 | |
| 14 | 2023 | 54 | |
| 15 | 2022 | 75 | |
| 16 | 2021 | 69 | |
| 17 | 2020 | 85 | |
| 18 | 2020 | 95 | |
| 19 | 2020 | 125 | |
| 20 | 2020 | 4 |
About Shaker El–Sappagh
Shaker El–Sappagh is a scholar working on Health Information Management, Health Informatics and Artificial Intelligence, having authored 146 papers that have together received 5.3k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (35 papers), Machine Learning in Healthcare (29 papers), Biomedical Text Mining and Ontologies (24 papers), Semantic Web and Ontologies (23 papers), COVID-19 diagnosis using AI (13 papers), AI in cancer detection (12 papers), Brain Tumor Detection and Classification (11 papers) and Anomaly Detection Techniques and Applications (9 papers). The work is most often cited by research in Health Informatics (403 citations), Health Information Management (1.0k citations) and Artificial Intelligence (2.3k citations). Shaker El–Sappagh has collaborated with scholars based in Egypt, South Korea and Saudi Arabia. Frequent co-authors include Farman Ali, Kyung Sup Kwak, Tamer Abuhmed, S. M. Riazul Islam, José M. Alonso, Amjad Ali, Daehan Kwak, Mohammed Elmogy, Muhammad Imran and Nora El-Rashidy. Their work appears in journals such as IEEE Access, Electronics, Computers, materials & continua/Computers, materials & continua (Print), Scientific Reports and Applied Sciences.
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.