An IoMT and Machine Learning Model Aimed at the Development of a Personalized Lifestyle Recommendation System Facilitating Improved Health

Abstract

The machine learning-based internet of medical things (IoMT) has recently gained traction in the healthcare industry because of its ability to reduce costs while simultaneously improving care quality through real-time and continuous monitoring. The advent of cutting-edge technologies has sparked a surge in interest in and demand for a more sophisticated healthcare delivery system. The chapter also shows software integration designs that are extremely important for the creation of smart healthcare systems. The developed systems are discussed in terms of their contributions, working procedures, results, and comparative merits and limits, all of which are included in the explanations. Existing system flaws and new framework introduction strategies are discussed, as well as current research difficulties and potential future paths. The goal is to give readers a thorough understanding of the most current advancements in the field of smart healthcare systems.