Ray, Ravi (2025) AI-enhanced wearable ecosystem: Transforming patient data into personalized healthcare interventions. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 1214-1222. ISSN 2582-8266
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Abstract
An innovative system relying on AI is introduced here to track health in real time using devices that can be worn. Compared to episodic care, the suggested system addresses these challenges by combining multiple kinds of physiological information within a layered structure of sensing, edge and cloud systems. Thanks to advanced machine learning and customized baseline calibration, the framework can find disease deterioration early and apply relevant help. Article analysis in different chronic conditions finds substantial progress in areas such as cutting hospital admissions, emergency department visits, better use of drugs as prescribed and higher quality of life. By applying edge computing, privacy-preserving methods and AI that can be explained, the article is helping healthcare move toward AI adoption. Unlike past approaches, this work encourages personalized and long-lasting treatment for chronic diseases, helping save the healthcare system significant money.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.3.0982 |
Uncontrolled Keywords: | Artificial Intelligence; Wearable Health Monitoring; Personalized Medicine; Edge Computing; Chronic Disease Management |
Depositing User: | Editor Engineering Section |
Date Deposited: | 16 Aug 2025 13:10 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4686 |