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IITM Journal of Information Technology

ISSN (P) 2395-5457 | Single Blind Peer Reviewed Journal

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INSTITUTE OF INNOVATION IN TECHNOLOGY & MANAGEMENT
Affiliated to GGSIPU, NAAC Grade ‘A’, ISO 14001:2015, 17020:2012, 21001:2018 & 50001:2018 Certified,
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Reinforcement Algorithm for Energy Harvesting & Task Allocation in Multi-Robot systems

Vandana Dabass
Assistant Professor, Institute of Innovation in Technology and Management
Author
 Suman Sangwan
Author

Keywords: Machine Learning (ML), Artificial Learning (AI), Natural Language Processing (NLP), Mental Health Disorder.

Abstract: Mental health disorders have emerged as one of the most formidable challenges of the 21st century, affecting nearly 970 million individuals worldwide [1], [2]. With the rapid advancement of artificial intelligence (AI) technologies, researchers and clinicians are increasingly harnessing these tools to enhance diagnostic accuracy, personalize therapeutic interventions, and expand access to mental health services [3], [4]. This review paper critically examines current AI-based tools that are transforming mental health care. In particular, we analyze machine learning algorithms, deep learning architectures, and natural language processing (NLP) applications in psychiatric diagnostics and therapy. Our analysis draws upon recent studies and meta analyses to present data-driven insights, illustrated with sample graphs and statistical findings. Moreover, ethical, privacy, and implementation challenges are discussed alongside future directions for integrating AI into mental health systems. Our review not only synthesizes the state-of-the-art research but also outlines a roadmap for future studies, ensuring that AI becomes a trusted partner in mental health care [5]–[8].

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