The Role of Artificial Intelligence and Machine Learning in Digital Health and Telemedicine Ecosystems: A Comprehensive Review

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have become essential technological drivers in Digital Health and Telemedicine, enabling more efficient clinical workflows, improved diagnostic accuracy, and optimized remote care delivery. With the growing adoption of Remote Patient Monitoring, Mobile Health (mHealth), Wearable Devices, and Internet of Medical Things (IoMT) ecosystems, AI-driven systems now play a crucial role in predictive analytics, personalized care, and intelligent clinical decision-making. This review provides an in-depth analysis of emerging AI/ML-powered digital health applications, technological advancements, clinical benefits, implementation challenges, and future opportunities. The paper synthesizes recent findings (2019–2025) from leading scientific literature and highlights the impact of AI on telehealth interventions, smart hospitals, digital therapeutics, virtual care, and health information systems. It further explores interoperability issues, privacy and security concerns, blockchain-based healthcare models, and policy implications for the next generation of digital health ecosystems.