The Electronic Health Record (EHR) systems provide health information about patients. Data security, integrity, and management of EHR are crucial problems. Records can be modified and altered by different stockholders as the different users may be using them in more than one form. We provide a new approach, methodology, and system for calculating dyslexia symptoms in this research with a machine learning algorithm and secure dyslexia data storage using blockchain technology. The major role of our paper is to test a primary-age group student against dyslexia, a student detected in such early years of his life for such a disability then he or she can be easily cured for the disabilities and can spend the rest of his life normally. For this, we will be using various machine learning algorithms. Dyslexic patterns and a large amount of data can be shared for future clinical research, statistical analysis, and quality assurance because the framework is language-independent and built on Blockchain and a decentralized big data repository. This paper presents the design, execution, and test results, demonstrating the dyslexia health management system's high potential for worldwide deployment using blockchain technology.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach, Volume , 1 January 2022,