Fatma Taher
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Radiomics and Machine Learning in Medical Imaging 17
- Retinal Imaging and Analysis 12
- COVID-19 diagnosis using AI 11
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- AI in cancer detection 24
- Co-authors
- Ayman El‐Baz (41 shared papers)Naoufel Werghi (16 shared papers)Hussain Al-Ahmad (23 shared papers)Hussam Al Hamadi (5 shared papers)Mohammed Ghazal (29 shared papers)Zhibo Zhang (2 shared papers)Ernesto Damiani (3 shared papers)Chan Yeob Yeun (2 shared papers)
- Journals
- IEEE Access (9 papers)Applied Sciences (6 papers)Frontiers in Bioscience-Landmark (3 papers)Scientific Reports (1 paper)Electronics (1 paper)
- Partner nations
- United Arab EmiratesUnited StatesEgypt
In The Last Decade
Fatma Taher
90 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Health Informatics 29
- Radiology, Nuclear Medicine and Imaging 483
- Neurology 130
- Computer Vision and Pattern Recognition 297
- Artificial Intelligence 464
Countries citing papers authored by Fatma Taher
This map shows the geographic impact of Fatma Taher'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 Fatma Taher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fatma Taher more than expected).
Fields of papers citing papers by Fatma Taher
This network shows the impact of papers produced by Fatma Taher. 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 Fatma Taher. The network helps show where Fatma Taher may publish in the future.
Co-authors
The 25 scholars most cited alongside Fatma Taher, 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research Hit paper breakdown → | 2022 | 172 |
| 2 | 2018 | 93 | |
| 3 | 2012 | 60 | |
| 4 | 2020 | 49 | |
| 5 | 2018 | 44 | |
| 6 | 2021 | 43 | |
| 7 | 2019 | 38 | |
| 8 | 2023 | 36 | |
| 9 | 2022 | 34 | |
| 10 | 2011 | 34 | |
| 11 | 2023 | 30 | |
| 12 | 2018 | 29 | |
| 13 | 2023 | 27 | |
| 14 | 2023 | 26 | |
| 15 | 2021 | 24 | |
| 16 | 2017 | 22 | |
| 17 | 2022 | 22 | |
| 18 | 2021 | 21 | |
| 19 | 2018 | 21 | |
| 20 | 2007 | 20 |
About Fatma Taher
Fatma Taher is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Aerospace Engineering, having authored 110 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Lung Cancer Diagnosis and Treatment (17 papers), Radiomics and Machine Learning in Medical Imaging (17 papers), Medical Image Segmentation Techniques (12 papers), Retinal Imaging and Analysis (12 papers), COVID-19 diagnosis using AI (11 papers), Brain Tumor Detection and Classification (11 papers) and Antenna Design and Analysis (10 papers). The work is most often cited by research in Health Informatics (29 citations), Radiology, Nuclear Medicine and Imaging (483 citations), Neurology (130 citations), Computer Vision and Pattern Recognition (297 citations) and Artificial Intelligence (464 citations). Fatma Taher has collaborated with scholars based in United Arab Emirates, United States and Egypt. Frequent co-authors include Ayman El‐Baz, Naoufel Werghi, Hussain Al-Ahmad, Hussam Al Hamadi, Mohammed Ghazal, Zhibo Zhang, Ernesto Damiani, Chan Yeob Yeun, Ahmed Soliman and Mohamed Elhoseny. Their work appears in journals such as IEEE Access, Applied Sciences, Frontiers in Bioscience-Landmark, Scientific Reports and Electronics.
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.