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Mohammad Khaleel Ma'aitah
PeerJ Reviewer
140 Points

Contributions by role

Reviewer 140

Contributions by subject area

Bioinformatics
Cardiology
Radiology and Medical Imaging
Computational Science
Data Mining and Machine Learning
Artificial Intelligence
Neural Networks
Computer Vision
Text Mining
Internet of Things

Mohammad Khaleel Ma'aitah

PeerJ Reviewer

Summary

Mohammad Maaitah is a Computer Engineer with extensive experience and management skills and works as a head of Department of Management Information Systems at Near East University, North Cyprus. As a Computer Engineer, he is not only responsible from the departmental duties but also currently involved in research projects as well. Additionally, he is a reviewer in various prestigious Journals such as Communication Biology, Nature and Journal of Medical Science Monitor and so forth. Mohammad Maaitah had his B.Sc in Computer Engineering from the University of Al Balqa, his M.sc Information Technology at Eastern Mediterranean University and Ph.D. at Near East University.

Artificial Intelligence Computer Vision

Work details

Assist.prof.Dr

Near East University
Management Information System

Websites

  • Google Scholar

PeerJ Contributions

  • Reviewed 3

Signed reviews submitted for articles published in PeerJ Note that some articles may not have the review itself made public unless authors have made them open as well.

February 26, 2024
RNN-BiLSTM-CRF based amalgamated deep learning model for electricity theft detection to secure smart grids
Aqsa Khalid, Ghulam Mustafa, Muhammad Rizwan Rashid Rana, Saeed M. Alshahrani, Mofadal Alymani
https://doi.org/10.7717/peerj-cs.1872
March 22, 2023
Epoch and accuracy based empirical study for cardiac MRI segmentation using deep learning technique
Niharika Das, Sujoy Das
https://doi.org/10.7717/peerj.14939 PubMed 36974136
May 27, 2021
An optimized transfer learning-based approach for automatic diagnosis of COVID-19 from chest x-ray images
Waleed M. Bahgat, Hossam Magdy Balaha, Yousry AbdulAzeem, Mahmoud M. Badawy
https://doi.org/10.7717/peerj-cs.555