A Survey of Machine Learning and IoT Integration in Personalized Healthcare
Abstract
Personalized healthcare aims to tailor medical treatment to individual characteristics, needs, and preferences. This paper surveys the integration of machine learning and IoT technologies in personalized healthcare. It covers various applications such as personalized treatment plans, real-time health monitoring, and adaptive intervention strategies. The survey highlights recent advancements, key challenges, and future research directions. Emphasis is placed on the potential of machine learning algorithms to analyze large volumes of health data generated by IoT devices, enabling more accurate and personalized healthcare solutions. The paper concludes with recommendations for overcoming current limitations and maximizing the benefits of these technologies in personalized healthcare.
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