M
Mohamed Hammad
Researcher at Menoufia University
Publications - 103
Citations - 2530
Mohamed Hammad is an academic researcher from Menoufia University. The author has contributed to research in topics: Medicine & Deep learning. The author has an hindex of 21, co-authored 76 publications receiving 1347 citations. Previous affiliations of Mohamed Hammad include City of Hope National Medical Center & King Abdulaziz City for Science and Technology.
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Progress in Outlier Detection Techniques: A Survey
TL;DR: This survey presents a comprehensive and organized review of the progress of outlier detection methods from 2000 to 2019 and categorizes them into different techniques from diverse outlier Detection techniques, such as distance-, clustering-, density-, ensemble-, and learning-based methods.
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Multimodal Biometric Authentication Systems Using Convolution Neural Network Based on Different Level Fusion of ECG and Fingerprint
TL;DR: A secure multimodal biometric system that uses convolution neural network (CNN) and Q-Gaussian multi support vector machine (QG-MSVM) based on a different level fusion to protect these templates and increase the security of the proposed system.
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Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections
Ahmed Sedik,Abdullah M. Iliyasu,Abdullah M. Iliyasu,Abdullah M. Iliyasu,Basma Abd El-Rahiem,Mohammed Elsayed Abdel Samea,Asmaa Abdel-Raheem,Mohamed Hammad,Jialiang Peng,Fathi E. Abd El-Samie,Ahmed A. Abd El-Latif,Ahmed A. Abd El-Latif +11 more
TL;DR: The proposed algorithm is effective in performing a rapid and consistent Corona virus diagnosis that is primarily aimed at assisting clinicians in making accurate identification of the virus.
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A Multitier Deep Learning Model for Arrhythmia Detection
TL;DR: A deep neural network strategy is presented to ameliorate the difficulties faced in ECG-based CVD diagnosis and treatment and suggests that the proposed model could serve as an analytic module to alert users and/or medical experts when anomalies are detected.
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Increasing drug solubility by means of bile salt–phosphatidylcholine-based mixed micelles
Mohamed Hammad,Bernd W. Müller +1 more
TL;DR: Study of the solubilization of commercial grades of soya phosphatidylcholine with different purities by bile salts indicated that only highly pure grades of SPC are suitable for the preparation of clear solutions of BS/ SPC-mixed micelles (BS/SPC-MM).