Mohammad Hashem Ryalat
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Computational Theory and Mathematics top 10%
- Biomedical Engineering
- Co-authors
- Hussein Al-ZoubiMalik BraikAzizi AbdullahRizik Al-SayyedOsama DorghamMohammed AlweshahAlaa ShetaNijad Al-Najdawi
- Topics
- Medical Image Segmentation Techniques (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Metaheuristic Optimization Algorithms Research (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaNeural Computing and ApplicationsArtificial Intelligence Review
- Partner nations
- JordanUnited Arab EmiratesAustralia
In The Last Decade
Mohammad Hashem Ryalat
17 papers receiving 379 citations
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 232
- Computer Vision and Pattern Recognition 80
- Radiology, Nuclear Medicine and Imaging 79
- Computational Theory and Mathematics 60
- Biomedical Engineering 33
Countries citing papers authored by Mohammad Hashem Ryalat
This map shows the geographic impact of Mohammad Hashem Ryalat'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 Mohammad Hashem Ryalat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Hashem Ryalat more than expected).
Fields of papers citing papers by Mohammad Hashem Ryalat
This network shows the impact of papers produced by Mohammad Hashem Ryalat. 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 Mohammad Hashem Ryalat. The network helps show where Mohammad Hashem Ryalat may publish in the future.
Co-authorship network of co-authors of Mohammad Hashem Ryalat
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Hashem Ryalat. A scholar is included among the top collaborators of Mohammad Hashem Ryalat 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 Mohammad Hashem Ryalat. Mohammad Hashem Ryalat 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 | 1 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 4 | |
| 7 | 22 | |
| 8 | 31 | |
| 9 | 11 | |
| 10 | 131 | |
| 11 | 0 | |
| 12 | 79 | |
| 13 | 23 | |
| 14 | 9 | |
| 15 | 30 | |
| 16 | 14 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 18 |
About Mohammad Hashem Ryalat
Mohammad Hashem Ryalat is a scholar working on Computer Graphics and Computer-Aided Design, Software and Radiology, Nuclear Medicine and Imaging, having authored 19 papers that have together received 389 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Metaheuristic Optimization Algorithms Research (4 papers). The work is most often cited by research in Artificial Intelligence (232 citations), Software (15 citations) and Computer Vision and Pattern Recognition (80 citations). Mohammad Hashem Ryalat has collaborated with scholars based in Jordan, United Arab Emirates and Australia. Frequent co-authors include Hussein Al-Zoubi, Malik Braik, Azizi Abdullah, Rizik Al-Sayyed, Osama Dorgham, Mohammed Alweshah, Alaa Sheta, Malik Braik, Nijad Al-Najdawi and Seyedali Mirjalili. Their work appears in journals such as SHILAP Revista de lepidopterología, Neural Computing and Applications and Artificial Intelligence Review.
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.