From prevention to management: exploring AI’s role in metabolic syndrome management: a comprehensive review - Udit Choubey; Vashishta Avadhani Upadrasta; Inder P. Kaur; Himanshi Banker; Sai Gautham Kanagala; F. N. U. Anamika; Mini Virmani; Rohit Jain (The Egyptian Journal of Internal Medicine)
Abstract Background This review aims to comprehensively explore the integration of artificial intelligence (AI) in the prevention, diagnosis, and treatment of metabolic syndrome (MetS). MetS is characterized by a cluster of conditions, posing a growing public health threat globally. Recognizing the limitations of traditional management approaches, we emphasize the potential of AI in transforming the management of MetS, focusing on recent advancements and applications in risk prediction and diagnosis. Body and conclusion. The integration of artificial intelligence in medicine is expanding, particularly in managing MetS, involving conditions like hypertension and dyslipidemia. Diagnosis and treatment challenges stem from addressing multiple conditions simultaneously. AI tools prove essential in monitoring indices such as blood pressure and glucose, and identifying trends for treatment adjustments. Lifestyle modifications are crucial, and AI can facilitate these changes through user-friendly interfaces and positive reinforcement. Standardization and successful implementation of AI tools in medical practices are necessary for revolutionizing MetS management, requiring focused future research efforts.