Title: Machine learning is revolutionising preventive healthcare and patient monitoring: a review

Authors: Yatin Kohli; Monika Kohli; Arun Kohli; M. Uma; Prabhu Sethuramalingam

Addresses: Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India ' Kalra Hospital, Kirti Nagar, New Delhi, India ' Life Span Wellness Diabetics and Cardio Metabolic Clinic, Janakpuri, New Delhi ' Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India ' Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India

Abstract: Machine learning (ML) integrated with wearable sensors and biosensors transforms healthcare by enabling continuous patient monitoring and early disease detection. These devices collect real-time vital sign data, including blood pressure, heart rate, and glucose levels, to identify patterns and abnormalities. ML algorithms analyse this data to detect chronic conditions like diabetes and cardiovascular diseases before clinical symptoms appear, reducing hospitalisations, emergency visits, and healthcare costs through a proactive approach. Wearable technology enhances personalised medicine by providing patient-specific health insights and actionable recommendations, such as real-time glucose monitoring to help diabetics adjust their diet and medication based on predictive analytics. Additionally, ML-driven systems assess lifestyle factors like activity levels, stress markers, and sleep patterns to predict potential health risks, improving clinical outcomes while optimising healthcare resource utilisation. AI-powered wearable systems ensure continuous adaptation and enhanced diagnostic accuracy over time. The fusion of ML and wearables is shaping the future of healthcare with a focus on personalisation, prevention, and efficiency.

Keywords: machine learning; ML; artificial intelligence; AI; chronic disease management; telemedicine; remote patient monitoring; RPM.

DOI: 10.1504/IJAIH.2025.149245

International Journal of Artificial Intelligence in Healthcare, 2025 Vol.1 No.1, pp.17 - 47

Received: 31 Dec 2024
Accepted: 22 Apr 2025
Published online: 20 Oct 2025 *