Role of Big Data, AI and Deep Learning in Medical Image Training Models and Decision Support System Using I4.0 Technologies

The area of diagnostic decision assistance in radiology is going through a rapid shift with the availability of a lot of patient information and the advancement of new AI (Artificial Intelligence) techniques of ML (Machine Learning), like DL (Deep Learning). They have the potential to offer imaging professionals tools that will increase the precision and effectiveness of diagnosis and therapy. This paper will discuss the development of the area of radiology and general trends emphasizing advancements in diagnostic decision assistance from the earliest rule-based expert systems to contemporary cognitive assistants utilizing I4.0 technology. The accuracy, dependability, and productivity of electronic equipment in the healthcare industry must be improved with the use of the IoMT (Internet of Medical Things). Researchers are building a digital healthcare system by connecting the already available medical resources and healthcare services. Although IoT is converging across many disciplines, our attention is on the scientific contributions of IoT in the healthcare domain. In terms of medical services in healthcare, this article discusses IoT applications, user contributions, and upcoming problems specifically in medical imaging hence the name Internet of Medical Imaging Things. It also gives a complete overview of the latest developments of ML approaches broadly utilized for Medical Imaging Diagnostic using I4.0 by classifying the study as per the ML methods, equipment, and machinery used and a foundation for future research.