Smart aging: integrating AI into elderly healthcare

Area of Science:

• Geriatric Medicine
• Medical Informatics
• Health Technology

Background:

• Aging populations present complex healthcare challenges including frailty, multimorbidity, and polypharmacy.
• Traditional healthcare models face limitations in addressing the unique needs of older adults.
• Artificial Intelligence (AI) offers potential solutions for improving care delivery in geriatrics.

Purpose of the Study:

• To provide a comprehensive overview of AI applications in geriatric medicine.
• To discuss the benefits and limitations of AI integration in elderly care.
• To explore future directions for AI in supporting healthy aging.

Main Methods:

• Review of current AI technologies in geriatric healthcare, including machine learning (ML) algorithms, predictive analytics, and robotics.
• Analysis of AI's role in disease detection, patient management, and clinical decision-making.
• Examination of challenges and ethical considerations associated with AI implementation.

Main Results:

• AI tools demonstrate potential for personalized medicine, enhanced diagnostic accuracy, and streamlined healthcare administration.
• AI can aid in fall prevention, frailty assessment, and managing complex conditions in older adults.
• Key challenges include data privacy, algorithmic bias, ethical concerns, and digital literacy gaps.

Conclusions:

• Responsible AI integration can significantly improve patient outcomes, reduce hospital readmissions, and support aging in place.
• Addressing challenges requires interdisciplinary collaboration, policy development, and diverse datasets to ensure equitable care.
• AI should complement, not replace, human clinical expertise in geriatric settings.