AI-Driven Predictive Models and Machine Learning Applications in Geriatric Care: From Fall Detection to Chronic Disease Management and Patient-Centric Solutions
International Journal of Engineering and Techniques – Volume 10 Issue 1, Jan – Feb 2024
ISSN: 2395-1303 | www.ijetjournal.org
Durai Rajesh Natarajan1, Dharma Teja Valivarthi2, Swapna Narla3, Sreekar Peddi4, Sai Sathish Kethu5
1 Estrada Consulting Inc, California, USA | Email: durairajeshnatarajan@gmail.com
2 Tek Leaders, Texas, USA | Email: teja89.ai@gmail.com
3 Tek Yantra Inc, California, USA | Email: swapnanarla8883@gmail.com
4 Tek Leaders, Texas, USA | Email: sreekarpeddi95@gmail.com
5 NeuraFlash, Georgia, USA | Email: skethu86@gmail.com
Abstract
With an aging population facing higher risks of falls and chronic diseases, AI-driven predictive models and machine learning solutions offer transformative advancements in elderly care. Traditional healthcare often reacts to crises, necessitating proactive AI-based solutions to anticipate risks, optimize treatments, and improve patient outcomes. This study explores various AI applications in geriatric care, including fall detection systems, predictive chronic disease management, and personalized patient-centric approaches to enhance healthcare services.
Keywords
AI in elderly care, predictive analytics, chronic disease management, machine learning in healthcare, patient-centric AI solutions
How to Cite
Durai Rajesh Natarajan, Dharma Teja Valivarthi, Swapna Narla, Sreekar Peddi, Sai Sathish Kethu, “AI-Driven Predictive Models and Machine Learning Applications in Geriatric Care,” International Journal of Engineering and Techniques, Volume 10, Issue 1, Jan – Feb 2024. ISSN 2395-1303
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