Smart aging: integrating AI into elderly healthcare

Clinical Snapshot

Key Findings

• Effect Size: Not quantified - narrative synthesis only

• Primary Outcome: AI shows promise in improving geriatric healthcare through enhanced diagnostics, personalized medicine, and workflow optimization

• Nnt Or Sensitivity: Not reported - review does not provide specific diagnostic accuracy metrics

• Confidence Interval: Not provided

Clinical Application

Implementation requires significant infrastructure investment, staff training, and addressing digital literacy gaps Relevant to Australian aged care sector, particularly given government investment in digital health initiatives and the Royal Commission recommendations for aged care reform Elderly patients in various healthcare settings, particularly those with multimorbidity and complex care needs

Abstract

Artificial Intelligence (AI) is transforming geriatric healthcare by improving early disease detection, optimizing patient management, and enhancing clinical decision-making. AI-driven tools, including machine learning (ML) algorithms, predictive analytics, and assistive robotics, are increasingly utilized to address challenges associated with aging, such as frailty, multimorbidity, polypharmacy, and fall prevention. These technologies can facilitate personalized medicine, improve diagnostic accuracy, and support healthcare administration by streamlining workflows and resource allocation. Despite its promising applications, the integration of AI in geriatric care presents several challenges, including issues related to data privacy, algorithmic bias, ethical considerations, and the digital literacy of older adults. Ensuring the inclusivity of AI models by incorporating diverse and representative datasets is essential to avoid disparities in healthcare delivery. Additionally, the role of AI must be carefully regulated to complement, rather than replace, human clinical expertise. This paper provides a comprehensive overview of AI applications in geriatric medicine, discussing its benefits, limitations, and future directions. By leveraging AI responsibly, healthcare systems can improve patient outcomes, reduce hospital readmissions, and promote aging in place. However, addressing existing challenges through interdisciplinary collaboration, policy development, and continued research is crucial to fully realizing AI's potential in elderly care.

References

1. 1.Tana, C., Siniscalchi, C., Cerundolo, N., Meschi, T., Martelletti, P., Tana, M., Moffa, L., Wells-Gatnik, W., Cipollone, F., & Giamberardino, M. A. (2025). Smart aging: integrating AI into elderly healthcare. BMC Geriatr. https://doi.org/10.3389/fpsyg.2024.1390182