Smart Approaches for Diagnosis of Brain Disorders Using Artificial Intelligence

Abstract

Modern health care thrives to create efficient medical processes, improving current medical facilities by automating them for additional benefits for healthcare systems.Disease diagnosis has always been a matter of concern for health professionals, as manual evaluation of medical data is tiresome and prone to errors. The revolution in Artificial Intelligence has paved the way for automatic detection and diagnosis of disease. The brain is the most important organ of the human body, as it acts as the command and coordination centre; therefore, brain disorder diagnosis is the major research area where AI techniques for digitization and automation are being employed. Use of deep learning in diagnostic procedures has produced promising results in diagnosis of neurological disorders and precision medicine. This chapter will present an overview of the current literature on AI techniques being employed in brain care and diagnosis. It will also summarize the importance of AI in healthcare in terms of its clinical use in disease classification and subsequent diagnosis and predictive medicine. This chapter discusses principal modalities and knowledge representation used in neuroscience for analysis, thereby gaining insight into the structural functionality of AI systems. Furthermore, we briefly explain the recent classification methods used in brain disorder diagnosis and their potential for transforming brain care in line with recent breakthroughs in deep learning. We will discuss the main data types used for brain disorder diagnosis, data-specific AI techniques deployed for solving brain-related tasks, the methodology used for evaluating state-of-the-art diagnostic systems, and the algorithms being implemented to make classifications.