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Mohammed A. Hadwan

Work place: Department of IT, College of Computer, Qassim University, Buraidah, Saudi Arabia

E-mail: M.hadwan@qu.edu.sa

Website:

Research Interests: Speech Recognition, Speech Synthesis, Data Structures and Algorithms, Analysis of Algorithms, Combinatorial Optimization, Mathematics of Computing

Biography

Mohammed A. Hadwan: received his B.Sc in Computer science from National University, Taiz Yemen in 2003. Then got his MSc in Computer Science from School of Computer Sciences, University Science Malaysia (USM), Penang Malaysia in 2006. Dr. Hadwan completed his Ph.D. in Computer Science and Information Technology (Artificial Intelligence), from Faculty of Information Science and Technology, National University Malaysia (UKM) in 2012. He was the Dean of Engineering and Information Technology College, Saeed University Taiz-Yemen from March 2012 until December 2015 and the head of Computer Science department, Faculty of Applied Sciences, Taiz University from May 2014 until March 2016. Currently, he is a staff member at the Information Technology department at the College of Computer, Qassim University. Dr. Hadwan is now the head of the accreditation committee and the program manager of B.Sc degree at Information Technology department. His current research interests include AI algorithms and applications in general. Optimization, Big data, internet of things, speech recognition and E-business and E-commerce are among his interest research areas. Dr. Hadwan is member of IEEE, Data Mining and optimization group DMO and Intelligent and Analytics group (IAG). He is an active researcher and a reviewer of several international and local journals.

Author Articles
Knowledge Extraction Methods as a Measurement Tool of Depression Discovery in Saudi Society

By Mohammed Abdullah Al-Hagery Sara Saleh Alfaozan Hajar Abdulrahman Alghofaily Mohammed A. Hadwan

DOI: https://doi.org/10.5815/ijitcs.2020.04.01, Pub. Date: 8 Aug. 2020

Depression is a widespread and serious phenomenon in public health in all societies. In Saudi society, depression is one of the diseases that the community is may refuse to disclose it. There are no studies have analyzed this disease within the Saudi community. The main research objective is to discover the depression level of Saudi People's. In addition to analyzing the age group and the most gender type affected by the depression in this society. The data collected from social media achieved indirectly without any communication with patients as a sample from this society people. It analyzed using Machine Learning algorithms that give accurate results for this disease. Three classification models have been established to diagnose this disease and the findings of this study presented that the depression levels include five ‎classes and ‎the most affected age group in depression was in the ‎age group from 20-26 years. The results show that young Saudi women are more likely to be depressed. The obtained results are very important to the medical field. Researchers and people working in this field can get benefits out of this research. Especially those who want to understand the depression disease in Saudi society and searching for real solutions to overcome this problem.

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