Applications of AI in the management of elderly diabetes patients

The prevalence of diabetes among the elderly population has been rising rapidly. Elderly individuals with diabetes frequently exhibit atypical symptoms, and face an increased risk of severe complications, comorbidities and geriatric syndromes, including hypoglycemia, sarcopenia, cognitive impairment, depression, and falls. These issues not only diminish quality of life, but also contribute to elevated disease burden. Conventional diabetes management strategies for this population often fall short due to their invasive nature, limited capacity for real-time monitoring, and poor patient adherence. The emergence of artificial intelligence (AI) in medicine offers a transformative solution to these challenges. Fueled by large-scale datasets, advanced machine learning algorithms, and state-of-the-art computational techniques, AI enables non-invasive, real-time monitoring systems and delivers personalized diagnostic and treatment solutions for this population. This review comprehensively explores the role of AI in managing diabetes and its comorbid conditions among older adults, highlighting its applications in screening, diagnostic, monitoring, and therapeutic strategies. It also addresses the practical challenges and ethical considerations of integrating AI into clinical practice.