Prevention and diagnosis of neurodegenerative diseases using machine learning models

Studies have revealed that neurodegenerative diseases known to cause cognitive impairment will increase significantly worldwide by 2050. Subsequently, there is a critical need to utilize machine learning (ML) to analyze medical and health data to improve diagnosis, classification, and treatment of neurodegenerative diseases. With the rapid development of computational approaches, different knowledge-driven and data-driven models in artificial intelligence (AI) and clinical practice can be utilized to overcome challenges in understanding, diagnosing, and preventing neurodegenerative disease. The development of biosensor technologies that use preprocessing of data, data collection, ML classifiers, and feature extraction has allowed timely detection of many neurodegenerative diseases. Thus, this chapter elaborates on the importance of ML techniques for diagnosing and preventing neurodegenerative diseases.