The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Mohamed Abdel-Mottaleb sits on this spectrum.
This scientist: 185 publications — 41st percentile
41% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Mohamed Abdel-Mottaleb sits on this spectrum.
This scientist: 50 D-Index — 62nd percentile
62% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Mohamed Abdel-Mottaleb is affiliated with the University of Miami in the United States. Their research spans multiple fields primarily centered around medicine and computer science, with a significant focus on the intersection of artificial intelligence and medical imaging.
Their work covers several subfields including radiology, nuclear medicine and imaging, computer vision and pattern recognition, artificial intelligence, biomedical engineering, and ophthalmology. This multidisciplinary approach contributes to a diverse set of research themes within the broader domains of healthcare and technology.
Key topics in Mohamed Abdel-Mottaleb's research portfolio include:
Their publication record includes research articles in prominent journals and conferences. Recent papers authored or co-authored by Mohamed Abdel-Mottaleb are:
Frequent publication venues for Mohamed Abdel-Mottaleb include Brain Stimulation, SSRN Electronic Journal, Computers in Biology and Medicine, IEEE Transactions on Image Processing, and Multimedia Tools and Applications.
The scientist has collaborated notably with several researchers, including:
Overall, the research contributions of Mohamed Abdel-Mottaleb integrate advanced machine learning techniques with medical imaging to address diagnostic challenges in areas such as cancer detection, glaucoma assessment, and arterial calcification identification. Their work emphasizes the application of AI-driven approaches to improve diagnostic accuracy and tool development within clinical contexts.
Rein-Lien Hsu;M. Abdel-Mottaleb;A.K. Jain
Mohammad Haghighat;Mohamed Abdel-Mottaleb;Wadee Alhalabi
Mohammad Haghighat;Saman Aliari Zonouz;Mohamed Abdel-Mottaleb
Nevenka Dimitorva;Mohamed S. Abdel-Mottaleb
Omaima Nomir;Mohamed Abdel-Mottaleb
Jindan Zhou;Mohamed Abdel-Mottaleb
M. Shneier;M. Abdel-Mottaleb
Gandhimathi Vaithilingam;Mohamed S. Abdel-Mottaleb
Mohamed Saeed Abdel-Mottaleb;Michael O. Shneier
Leila Abdelrahman;Manal Al Ghamdi;Fernando Collado-Mesa;Mohamed Abdel-Mottaleb
Mohammad Haghighat;Saman Aliari Zonouz;Mohamed Abdel-Mottaleb
Mohammad Haghighat;Mohamed Abdel-Mottaleb;Wadee Alhalabi
Jan Elenbaas;Nevenka Dimitrova;Thomas McGee;Mark Simpson
Ranjit Desai;Mohamed Abdel-Mottaleb
Gandhimathi Vaithilingam;Mohamed Abdel-Mottaleb
Mohammad H. Mahoor;Mohamed Abdel-Mottaleb
O. Nomir;M. Abdel-Mottaleb
M. Saif;Magdy Shebl;A.I. Nabeel;R. Shokry
Mohamed Abdel-Mottaleb;Jindan Zhou
S. Krishnamachari;M. Abdel-Mottaleb
M. Abdel-Mottaleb;A. Elgammal
A.-N. Ansari;M. Abdel-Mottaleb
Rein-Lien Hsu;M. Abdel-Mottaleb;A.K. Jain
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