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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- AI in cancer detection 7
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- Cancer Genomics and Diagnostics 5
- Breast Cancer Treatment Studies 4
- Co-authors
- Emad A. Rakha (20 shared papers)Po-Hsuan Cameron Chen (1 shared paper)Mohammed M. Abdelsamea (1 shared paper)Craig H. Mermel (1 shared paper)Ronnachai Jaroensri (1 shared paper)Paul Gamble (1 shared paper)Michael S. Toss (19 shared papers)Ayat Lashen (9 shared papers)
- Journals
- Histopathology (4 papers)Modern Pathology (4 papers)Cancers (3 papers)European Journal of Cancer (2 papers)npj Precision Oncology (1 paper)
- Partner nations
- United KingdomEgyptQatar
In The Last Decade
Asmaa Ibrahim
22 papers receiving 299 citations
Peers
Comparison fields: 5 of 57
- Health Informatics 28
- Radiology, Nuclear Medicine and Imaging 122
- Cancer Research 69
- Artificial Intelligence 166
- Oncology 73
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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 139 | |
| 2 | 2023 | 27 | |
| 3 | 2021 | 23 | |
| 4 | 2021 | 17 | |
| 5 | 2023 | 17 | |
| 6 | 2021 | 14 | |
| 7 | 2023 | 12 | |
| 8 | 2022 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2023 | 2 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2023 | 1 | |
| 20 | 2023 | 1 |
About Asmaa Ibrahim
Asmaa Ibrahim is a scholar working on Artificial Intelligence, Cancer Research, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Oncology, having authored 24 papers that have together received 308 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer Genomics and Diagnostics (5 papers), Breast Cancer Treatment Studies (4 papers), Cancer Cells and Metastasis (3 papers), Epigenetics and DNA Methylation (1 paper), Digital Imaging for Blood Diseases (1 paper) and Enhanced Recovery After Surgery (1 paper). The work is most often cited by research in Health Informatics (28 citations), Radiology, Nuclear Medicine and Imaging (122 citations), Cancer Research (69 citations), Artificial Intelligence (166 citations) and Oncology (73 citations). Asmaa Ibrahim has collaborated with scholars based in United Kingdom, Egypt and Qatar. Frequent co-authors include Emad A. Rakha, Po-Hsuan Cameron Chen, Mohammed M. Abdelsamea, Craig H. Mermel, Ronnachai Jaroensri, Paul Gamble, Michael S. Toss, Ayat Lashen, Ayaka Katayama and Fayyaz Minhas. Their work appears in journals such as Histopathology, Modern Pathology, Cancers, European Journal of Cancer and npj Precision Oncology.
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.