Machine Learning-Based Predictive Analytics in Healthcare IoT

Abstract

In the rapidly expanding field of healthcare IoT, predictive analytics powered by machine learning are becoming increasingly valuable. This research provides a comprehensive strategy for utilizing data analytics to provide preventative and individualized healthcare. The proposed research aims to advance IoT in the healthcare industry by addressing data preparation, feature engineering, model selection, and evaluation issues. The objective is to improve healthcare delivery and patient outcomes by developing more precise KNN (K Nearest Neighbor) prediction models. KNN has outperformed the existing methods with an accuracy of 98.4%. Future research should prioritize scalability and implementation of the proposed technique in operational healthcare IoT systems, keeping data privacy, security, and interoperability in mind.