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.
Keywords: Artificial intelligence, Biology, Block chain, Environment, Machine learning, Privacy, Psychiatry, Personalisation.
