AI and Edge Analytics for Real-Time IoT Decision-Making in SMAC Environments: A Comprehensive Review

Abstract

The integration of computational intelligence in modern healthcare has ushered in transformative advancements across various domains, significantly enhancing diagnosis, treatment, and patient care. This review explores recent progress in three critical areas: drug repurposing, mental health monitoring, and clinical decision support systems. Drug repurposing leverages large-scale biological and chemical data to identify new therapeutic applications for existing medications, offering a faster and costeffective pathway to treatment development. In the realm of mental health, digital tools combined with physiological and behavioral data are being used to detect early symptoms, monitor patient progress, and personalize therapeutic interventions. Furthermore, clinical decision support systems are playing a vital role in assisting healthcare professionals by synthesizing patient history, laboratory results, and medical guidelines to recommend accurate and timely interventions. These systems not only reduce diagnostic errors but also improve workflow efficiency and patient outcomes. The review critically examines key methodologies, practical implementations, and real-world applications, while also addressing ethical challenges, data privacy concerns, and regulatory considerations. By synthesizing current research and healthcare practices, this article aims to provide a comprehensive overview of how advanced computational techniques are reshaping the delivery of healthcare services.

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