Ahmed Alksas
Impact in
- Health Informatics top 10%
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 21
- COVID-19 diagnosis using AI 7
- MRI in cancer diagnosis 5
-
- Lung Cancer Diagnosis and Treatment 6
- Renal cell carcinoma treatment 5
- Co-authors
- Ayman El‐Baz (40 shared papers)Mohamed Shehata (21 shared papers)Mohammed Ghazal (33 shared papers)Ahmed Abdel Khalek Abdel Razek (5 shared papers)Ali Mahmoud (19 shared papers)Hadil Abu Khalifeh (5 shared papers)Sohail Contractor (16 shared papers)Ahmed Soliman (5 shared papers)
- Journals
- IEEE Access (4 papers)Cancers (3 papers)Scientific Reports (3 papers)Biomedicines (2 papers)Computer Methods and Programs in Biomedicine (2 papers)
- Partner nations
- United StatesUnited Arab EmiratesEgypt
In The Last Decade
Ahmed Alksas
38 papers receiving 358 citations
Peers
Comparison fields: 5 of 54
- Health Informatics 16
- Radiology, Nuclear Medicine and Imaging 178
- Neurology 44
- Genetics 46
- Computer Vision and Pattern Recognition 66
Countries citing papers authored by Ahmed Alksas
This map shows the geographic impact of Ahmed Alksas'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 Ahmed Alksas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed Alksas more than expected).
Fields of papers citing papers by Ahmed Alksas
This network shows the impact of papers produced by Ahmed Alksas. 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 Ahmed Alksas. The network helps show where Ahmed Alksas may publish in the future.
Co-authors
The 25 scholars most cited alongside Ahmed Alksas, 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 82 | |
| 2 | 2021 | 40 | |
| 3 | 2021 | 24 | |
| 4 | 2023 | 23 | |
| 5 | 2022 | 17 | |
| 6 | 2023 | 13 | |
| 7 | 2022 | 12 | |
| 8 | 2023 | 12 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 11 | |
| 11 | 2022 | 9 | |
| 12 | 2023 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 8 | |
| 15 | 2023 | 7 | |
| 16 | 2024 | 7 | |
| 17 | 2023 | 7 | |
| 18 | 2024 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2024 | 5 |
About Ahmed Alksas
Ahmed Alksas is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Biomedical Engineering, Molecular Biology and Artificial Intelligence, having authored 42 papers that have together received 359 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (21 papers), COVID-19 diagnosis using AI (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), Renal cell carcinoma treatment (5 papers), MRI in cancer diagnosis (5 papers), AI in cancer detection (5 papers), Advanced X-ray and CT Imaging (4 papers) and Renal and related cancers (4 papers). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (178 citations), Neurology (44 citations), Genetics (46 citations) and Computer Vision and Pattern Recognition (66 citations). Ahmed Alksas has collaborated with scholars based in United States, United Arab Emirates and Egypt. Frequent co-authors include Ayman El‐Baz, Mohamed Shehata, Mohammed Ghazal, Ahmed Abdel Khalek Abdel Razek, Ali Mahmoud, Hadil Abu Khalifeh, Sohail Contractor, Ahmed Soliman, Ahmed Shaffie and Hossam Magdy Balaha. Their work appears in journals such as IEEE Access, Cancers, Scientific Reports, Biomedicines and Computer Methods and Programs in Biomedicine.
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.