European Journal of Biomedical and Pharmaceutical Sciences

THE ROLE OF ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH CARE: INNOVATIONS, CHALLENGES AND FUTURE DIRECTIONS

*Sathya S. R., Ranga Priya M., Gunasundari T. and Manivannan R.

ABSTRACT

Artificial Intelligence (AI) is reshaping mental healthcare delivery by offering innovative solutions to enhance diagnosis, treatment, and management of mental health disorders. This review article explores the multifaceted role of AI in mental health care, encompassing applications such as early detection, personalized interventions, remote monitoring, and predictive analytics. Machine learning algorithms analyze diverse datasets, including electronic health records, wearable sensor data, and social media activity, to detect patterns and predict outcomes, enabling early identification and intervention for individuals at risk of mental health conditions. Natural language processing systems facilitate virtual counseling and psycho-education through chatbots and conversational agents, extending access to mental health support services. Moreover, predictive analytics models inform care planning decisions and resource allocation, optimizing clinical decision-making and patient outcomes. Despite its potential benefits, the integration of AI in mental health care poses challenges related to privacy, data security, algorithmic bias, and regulatory compliance. Ethical guidelines, professional standards, and regulatory frameworks are essential to ensure the responsible and ethical use of AI technologies in mental health care. Looking ahead, the future of AI in mental health care holds promise for advancing precision medicine, personalized interventions, and population health management. Collaborative research efforts, interdisciplinary partnerships, and community engagement initiatives are needed to drive innovation, address disparities, and improve access to effective mental health care services for all individuals.

Keywords: Artificial Intelligence, Mental Health Care, Machine Learning, Natural Language Processing, Digital Therapeutics, Predictive Analytics, Challenges, Future Directions.