Asmaa Ibrahim
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Cancer Genomics and Diagnostics 5
- Breast Cancer Treatment Studies 4
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- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Emad A. Rakha (20 shared papers)Mohammed M. Abdelsamea (1 shared paper)Paul R Gamble (1 shared paper)Po-Hsuan Cameron Chen (1 shared paper)Michael S. Toss (19 shared papers)Craig H. Mermel (1 shared paper)Ronnachai Jaroensri (1 shared paper)Ayat Lashen (9 shared papers)
- Journals
- Modern Pathology (4 papers)Histopathology (4 papers)Cancers (3 papers)European Journal of Cancer (2 papers)The Journal of Pathology Clinical Research (2 papers)
- Partner nations
- United KingdomEgyptQatar
In The Last Decade
Asmaa Ibrahim
22 papers receiving 394 citations
Peers
Comparison fields: 5 of 60
- Health Informatics 36
- Radiology, Nuclear Medicine and Imaging 156
- Artificial Intelligence 223
- Cancer Research 83
- Biophysics 26
Countries citing papers authored by Asmaa Ibrahim
This map shows the geographic impact of Asmaa Ibrahim'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 Asmaa Ibrahim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Asmaa Ibrahim more than expected).
Fields of papers citing papers by Asmaa Ibrahim
This network shows the impact of papers produced by Asmaa Ibrahim. 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 Asmaa Ibrahim. The network helps show where Asmaa Ibrahim may publish in the future.
Co-authors
The 25 scholars most cited alongside Asmaa Ibrahim, 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 | 2019 | 152 | |
| 2 | 2022 | 42 | |
| 3 | 2023 | 28 | |
| 4 | 2021 | 28 | |
| 5 | 2021 | 20 | |
| 6 | 2023 | 20 | |
| 7 | 2021 | 16 | |
| 8 | 2022 | 14 | |
| 9 | 2023 | 13 | |
| 10 | 2023 | 13 | |
| 11 | 2023 | 13 | |
| 12 | 2023 | 11 | |
| 13 | 2023 | 7 | |
| 14 | 2023 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2024 | 5 | |
| 17 | 2024 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2023 | 1 |
About Asmaa Ibrahim
Asmaa Ibrahim is a scholar working on Cancer Research, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Oncology and Software, having authored 26 papers that have together received 402 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Cancer Genomics and Diagnostics (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Breast Cancer Treatment Studies (4 papers), Cancer Cells and Metastasis (3 papers), Digital Imaging for Blood Diseases (2 papers), Enhanced Recovery After Surgery (1 paper) and Software Engineering Research (1 paper). The work is most often cited by research in Health Informatics (36 citations), Radiology, Nuclear Medicine and Imaging (156 citations), Artificial Intelligence (223 citations), Cancer Research (83 citations) and Biophysics (26 citations). Asmaa Ibrahim has collaborated with scholars based in United Kingdom, Egypt and Qatar. Frequent co-authors include Emad A. Rakha, Mohammed M. Abdelsamea, Paul R Gamble, Po-Hsuan Cameron Chen, Michael S. Toss, Craig H. Mermel, Ronnachai Jaroensri, Ayat Lashen, Fayyaz ul Amir Afsar Minhas and Ayaka Katayama. Their work appears in journals such as Modern Pathology, Histopathology, Cancers, European Journal of Cancer and The Journal of Pathology Clinical Research.
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.