ABSTRACT
The exciting growth of Deep Learning (DL) and Cyber-physical Systems (CPS) has sparked much interest in the field of medicine and healthcare in recent years. Deep Neural Networks (DNN), mainly Recurrent Neural Networks (RNN) and Convolutional Neural Networks, have actually been proven to be extremely effective at handling text, speech, and image data. In several medical domains, neural networks have reached or indeed exceeded the ability of experienced practitioners. An integrated healthcare system is a critical component of interconnected livelihood. The Healthcare system is a fundamental human necessity, and an intelligent healthcare system is expected to generate multiple billion in revenue over the next few years. Artificial Intelligence (AI), IoT (Internet of Things), biomedical sensors, IOMT (Internet of Medical Things), Cloud and Edge computing, and finally a new breed of wireless communication technology are all constituents of the intelligent healthcare systems. The sensors in massive quantity are integrated into IoMT, generating enormous volumes of data that can be used for a variety of purposes. DL would surely contribute to the generation of important insights from these large data repositories, hence assisting in the development of intelligent IoMT. In this context, examining the propensity of DL for IoMT predictive analytics gets critical. Data analysis is the method of analyzing each piece of information to uncover trends, unearth buried knowledge, and derive valuable information. The primary goal of IoMT data analytical platforms is to improve the clarity of data to facilitate the development of efficient operating actions. These choices can be used to support and maintain a wide variety of applications. An essential factor of the IoMT system is a competent data analysis method capable of performing actions such as regression, clustering, and classification. DL has indeed been intensively utilized to analyze information recorded by IoMT technology. Both DL and IoMT are identified as the most essential conservative innovative technologies for the biomedical sector. CPS are used in order to efficiently solve the reliability, robustness, security, modeling, verification and validation challenges of IoMT.
