Artificial Intelligence in Preventive Medicine and Chronic Disease Management: Key Roles and Limits

C. A. Korie, F. Onyekwuo, A. Emesowum, C. Vincent, J. Ibebuike, Nwagwu SA

Artificial intelligence (AI) in modern healthcare is one of the most transformational technologies available, giving unparalleled prospects to advance preventative medicine and treat chronic diseases. AI enhances healthcare systems’ ability to identify diseases earlier, predict health risks, tailor preventive interventions and improve longterm patient management by integrating machine learning, deep learning, natural language processing, computer vision and predictive analytics into clinical practice. with preventive medicine, AI helps with population health surveillance, risk stratification, precision screening, vaccination planning, lifestyle modification, and early identification of those at high risk for chronic illnesses. AI-powered clinical decision support systems, wearable health devices, remote patient monitoring, and digital therapeutics have demonstrated considerable potential in chronic disease management by improving disease control, reducing hospitalisations, enhancing medication adherence, and supporting personalised treatment strategies for conditions including diabetes mellitus, hypertension, cardiovascular disease, chronic kidney disease, chronic respiratory diseases, cancer, and mental health disorders. Despite these developments, widespread implementation is still impeded by significant challenges, including concerns about data privacy and security, algorithmic bias, a lack of transparency in complex AI models, limited interoperability with current health information systems, regulatory uncertainty, ethical concerns, and disparities in digital health infrastructure, particularly in low- and middle-income countries. Moreover, the successful integration of AI in healthcare requires professional monitoring, the preservation of patient autonomy and equal access to AI-enabled devices. This review critically examines the evolving role of artificial intelligence in preventive medicine and chronic disease management, discusses current applications and emerging innovations, assesses current limitations and ethical concerns, and discusses future directions for responsible, evidence-based, and patient-centered implementation of artificial intelligence into healthcare systems worldwide.