Advancing Data Science: A New Ray of Hope to Mental Health Care

Abstract

Mental health care has unique challenges and needs, unlike other medical fields. Complex biopsychosocial causation of psychiatric disorders demands advanced computational models for scientific probing. Artificial intelligence and machine learning (AI/ML) are showing promising leads in improvising psychiatry nosology, which in the current state lacks biological validity. Increasing mental health care needs can be addressed only with the appropriate use of advancing technologies. Increased accessibility to personal digital devices demonstrates the scope for sensitive behavioral evaluation amidst gathering large amounts of data. Patterns in, thus acquired, digital phenotypes can be effectively evaluated only through big data analysis techniques. This has the potential to open newer avenues of preventive as well as therapeutic psychiatry. Unique legal and ethical conundrums in clinical and research domains of psychiatry arise while managing one of the most vulnerable populations with health care needs, who may often approach facilities in a state of illness, unawareness, and diminished decision-making capacity. Secure blockchain technology amalgamating with AI/ML can enhance the applicability in such conditions in improving compliance, individualizing treatment, and enhancing research without compromising ethical standards. AI/ML is hoped to guide Interventional psychiatry, an evolving promising field that relies on neuroscientific approaches using multimodal data and neuromodulation techniques. The current chapter reviews the contributions of AI/ML and blockchain in various mental healthcare system domains; and proposes its potential in many other uncharted territories in this field.