ProfessorsProfessors of Alexandria UniversityMohamed A. Ismail

Mohamed A. Ismail

Alexandria University

H-index: 24

Africa-Egypt

About Mohamed A. Ismail

Mohamed A. Ismail, With an exceptional h-index of 24 and a recent h-index of 14 (since 2020), a distinguished researcher at Alexandria University, specializes in the field of Pattern Recognition, Computer Vision, Data Mining, Machine Learning, Computers in Medicine.

His recent articles reflect a diverse array of research interests and contributions to the field:

EVALUATION OF THE CURATIVE EFFECTS OF ZINC OXIDE NANOPARTICLES ON SOLANUM MELONGENA L. UNDER FLUORIDE STRESS.

EKNN: Ensemble classifier incorporating connectivity and density into kNN with application to cancer diagnosis

High Performance Computing for Detecting Complex Diseases using Deep Learning

Automatic Breast Cancer Classification from Histopathological Images

Mohamed A. Ismail Information

University	Alexandria University
Position	Professor of Computer Science Faculty of Engineering
Citations(all)	3978
Citations(since 2020)	878
Cited By	3438
hIndex(all)	24
hIndex(since 2020)	14
i10Index(all)	45
i10Index(since 2020)	15
Email	Access Email
University Profile Page	Alexandria University
Google Scholar	View Google Scholar Profile

Mohamed A. Ismail Skills & Research Interests

Pattern Recognition

Computer Vision

Data Mining

Machine Learning

Computers in Medicine

Top articles of Mohamed A. Ismail

Title	Journal	Author(s)	Publication Date
EVALUATION OF THE CURATIVE EFFECTS OF ZINC OXIDE NANOPARTICLES ON SOLANUM MELONGENA L. UNDER FLUORIDE STRESS.	Fluoride	Shakil Ahmed Mariam Fatima Madeeha Ansari Sundas Baba Rehana Sardar ...	2023/10/1
EKNN: Ensemble classifier incorporating connectivity and density into kNN with application to cancer diagnosis	Artificial Intelligence in Medicine	Mohamed A Mahfouz Amin Shoukry Mohamed A Ismail	2021/1/1
High Performance Computing for Detecting Complex Diseases using Deep Learning		Sahar I Ghanem Ahmed A Ghoneim Nagia M Ghanem Mohamed A Ismail	2020/2/10
Automatic Breast Cancer Classification from Histopathological Images		Fatma Anwar Omneya Attallah Nagia Ghanem Mohamed A Ismail	2020/2/10