Artificial Intelligence and Machine Learning Approach Recommendation System in Internet of Medical Things

Healthcare is rapidly advancing in the field of the Internet of Things (IoT). In the realm of the Internet of Medical Things (IoMT), a plethora of medical data is generated from various devices such as wearables, sensors, and medical imaging tools. An intelligent recommendation system for healthcare professionals becomes imperative in this context. These devices generate massive amounts of patient health data, allowing for personalized healthcare solutions. The proposed work investigates the use of Artificial Intelligence and Machine Learning approaches to build smart recommendation systems for healthcare users. This enables to offer personalized and timely suggestions for treatments and preventive measures, thereby enhancing patient care and improving healthcare services and decision-making. Finally, the proposed scheme is implemented to evaluate the performance of system in terms of accuracy, training time, and recommendations.