Unveiling Frontiers: Hybrid Algorithmic Frameworks for AI-Driven Mental Health Interventions
DOI:
https://doi.org/10.70445/avjcs.2.1.2025.1-8Keywords:
AI-Driven Mental Health, Hybrid Algorithms, Machine Learning, Personalized Therapy, Mental Health Interventions, Computational FrameworksAbstract
The worldwide rise of mental health disorders demands new ways that combine medical practice with technology updates. Depression and anxiety mental health conditions have become widespread worldwide yet keep overburdening healthcare systems. Standard healthcare approaches cannot meet all patient needs because they need substantial resources and are hard to develop at scale. Hybrid algorithmic systems made of multiple processing methods represent a new way to bring together elements that past methods could not work with effectively. Our study examines how to build and validate hybrid mental health frameworks that help patients with mental issues. Through machine learning technologies these frameworks help create customized mental health intervention solutions that work for many people. The research analyzes how these frameworks can be adjusted to serve different mental health needs through their technical design components. This research studies data protection issues and algorithm fairness while proposing solutions to integrate nicely with clinical practice. Our study works to create a new type of mental health care while using technology ethically to bring better mental health results worldwide.
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