A Review of Machine Learning (ML) in the Internet of Medical Things (IOMT) in the Construction of a Smart Healthcare Structure

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Aafreen Qureshi, Shivangi Batra, Prashant Vats, Sandeep Singh, Manu Phogat, Anupam Kumar Sharma


Epidemics are widespread perhaps the persistent medical problem continues causing financial, physiological, and psychological havoc around the planet. All areas are affected, from universities to the medical system. Innovation, on either hand, has greatly simplified our life and current condition. Even though the pandemic outbreak had a negative impact, it also resulted in discoveries and concepts that helped many people get through the difficult times and finally helped us adapt to the changing norms. IoMT and machine intelligence are two domains that have enabled the application of smart and telehealthcare, as well as earlier diagnosis, management, and treatment of various ailments throughout fearful times. The goal of this systematic review is to look at how IoMT and AI may help support, secure, and improve the healthcare system. In this review article, we see quickly how these fields are lowering human labor and making remote medical surveillance possible. We also go through the IoMT's hardware platform, as well as its implementations and associated topics. We also want to talk about why, because of the security concerns, mainstream acceptance and adoption are sluggish. These sectors are continuing to provide fresh perspectives not just in the fight against the novel Coronavirus pandemic, but also in a variety of other disciplines. This study aims to provide a comprehensive overview of AI and machine learning as important methods in healthcare and related disciplines.

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