AliAsghar AkhavanMahdavi - Master Student in Computer Engineering, Khavaran Institute of Higher Education, Mashhad, Iran
Elham Mahdipour - Assistant Professor, Computer Engineering Department, Khavaran Institute of Higher Education, Mashhad, Iran.
MohammadAli Nahayati - Assistant Professor, Faculty of Medicine, University of Medical Sciences, Mashhad, Iran.

People of all ages are constantly faced with various challenges and stresses, and studies have shown that anxiety and stress can play a significant role in aggravating the symptoms of MS. Therefore, controlling nervous stress may contribute to controlling the disease. The purpose of this study is to investigate and evaluate different methods of disease diagnosis and monitoring of patients. Based on the research published over the past five years, it is possible to evaluate the effectiveness of different methods for detecting MS disease and categorize them into five categories, including machine learning, MRI image processing, questionnaires, patient monitoring, electronic health record systems and applications, and nanotechnology. The present research aims to investigate various aspects of MS disease. Study results indicate that different questionnaires can be utilized to monitor patients with MS, and their quality of life may be improved by recognizing their daily problems

Disease, Multiple Sclerosis, Machine Learning, Deep Learning, Monitoring.