Data-Driven Healthcare: Leveraging AI for Real-Time Monitoring and Predictive Care

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in modern healthcare, offering unprecedented opportunities to harness data for real-time monitoring, predictive care, and proactive medical decision-making. The increasing adoption of wearable devices, Internet of Medical Things (IoMT), and electronic health records (EHRs) generates vast volumes of real-time data streams. AI techniques such as machine learning, deep learning, and reinforcement learning have enabled the extraction of actionable insights, leading to improved diagnosis, personalized treatments, and reduced healthcare costs. However, integrating AI into data-driven healthcare presents challenges including data quality, system interoperability, patient privacy, and clinical validation. This paper explores the role of AI in enabling real-time monitoring and predictive care, highlighting technological foundations, case studies, and future prospects. It emphasizes that while AI holds the promise of transforming healthcare delivery from reactive to preventive, ensuring ethical, secure, and scalable adoption remains a pressing necessity.