Artificial intelligence for internet of things and enhanced medical systems

Abstract

Internet of things (IoT), Big Data, and artificial intelligence (AI) are related research fields that have a relevant impact factor on the design and development of enhanced personalized healthcare systems. This paper discussed the review of AI for IoT and medical systems, which include the usage and practice of AI methodology in different fields of healthcare. The literature review shows that four main areas use AI methodology in medicine, such as heart disease diagnosis, predictive methods, robotic surgery, and personalized treatment. The results confirm that k-nearest neighbors, support vector machine, support vector regression, Naive Bayes, linear regression, regression tree, classification tree, and random forest are the leading AI methods. These methods are mainly used for patient’s data analysis to improve health conditions. Robotic surgery systems such as Transoral Robotic Surgery and Automated Endoscopic System for Optimal Positioning lead to several advantages as these methods provide less aggressive treatments and provide better results in terms of blood loss and faster recovery. Furthermore, Internet of medical things addresses numerous health conditions such a vital biophysical parameters supervision, diabetes, and medical decision-making support methods.