Mohamed Shehata
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Pulmonary and Respiratory Medicine
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Co-authors
- Ayman El‐BazMohamed Abou El‐GharMohammed GhazalAhmed AlksasFahmi KhalifaAhmed SolimanAmy C. DwyerAhmed Abdel Khalek Abdel Razek
- Topics
- MRI in cancer diagnosis (22 papers)Radiomics and Machine Learning in Medical Imaging (18 papers)Fetal and Pediatric Neurological Disorders (11 papers)
- Partner nations
- EgyptUnited StatesUnited Arab Emirates
In The Last Decade
Mohamed Shehata
51 papers receiving 641 citations
Peers
Comparison fields: 5 of 71
- Radiology, Nuclear Medicine and Imaging 377
- Artificial Intelligence 152
- Pulmonary and Respiratory Medicine 142
- Computer Vision and Pattern Recognition 122
- Biomedical Engineering 107
Countries citing papers authored by Mohamed Shehata
This map shows the geographic impact of Mohamed Shehata'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 Mohamed Shehata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Shehata more than expected).
Fields of papers citing papers by Mohamed Shehata
This network shows the impact of papers produced by Mohamed Shehata. 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 Mohamed Shehata. The network helps show where Mohamed Shehata may publish in the future.
Co-authorship network of co-authors of Mohamed Shehata
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Shehata. A scholar is included among the top collaborators of Mohamed Shehata based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohamed Shehata. Mohamed Shehata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 14 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 13 | |
| 8 | 7 | |
| 9 | 22 | |
| 10 | 7 | |
| 11 | 12 | |
| 12 | 8 | |
| 13 | 9 | |
| 14 | 12 | |
| 15 | 38 | |
| 16 | 24 | |
| 17 | 4 | |
| 18 | 78 | |
| 19 | 14 | |
| 20 | 44 |
About Mohamed Shehata
Mohamed Shehata is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Instrumentation, having authored 55 papers that have together received 648 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (22 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Fetal and Pediatric Neurological Disorders (11 papers). The work is most often cited by research in Health Informatics (61 citations), Radiology, Nuclear Medicine and Imaging (377 citations) and Transplantation (31 citations). Mohamed Shehata has collaborated with scholars based in Egypt, United States and United Arab Emirates. Frequent co-authors include Ayman El‐Baz, Mohamed Abou El‐Ghar, Mohammed Ghazal, Ahmed Alksas, Fahmi Khalifa, Ahmed Soliman, Amy C. Dwyer, Ahmed Abdel Khalek Abdel Razek, Ali Mahmoud and Ahmed Shalaby. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.
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.