Artificial Intelligence in Gerontology: Data-Driven Health Management and Precision Medicine

Abstract

As the global population ages, healthcare systems face increasing challenges in managing the complex health needs of older adults, including multimorbidity, cognitive decline, and frailty. Artificial intelligence (AI) holds significant potential to address these challenges by offering advanced tools for personalized health management, disease prediction, and real-time monitoring. This paper reviews key AI applications in gerontology, focusing on its role in analyzing multimodal data such as electronic health records, genomic data, medical imaging, and wearable device metrics. AI’s ability to integrate and analyze these diverse data types enhances the precision of disease management and treatment personalization, particularly in chronic disease care and cognitive function assessment. However, challenges related to data quality, privacy concerns, and model interpretability remain. This review highlights both the transformative potential and the limitations of AI in elderly healthcare, advocating for future research aimed at improving model transparency, scalability, and interdisciplinary integration to enhance geriatric care.

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