An Intelligent Collaborative Image-Sensing System for Disease Detection

With the growth of smart medical devices and applications in smart hospitals, home care facilities, nursing, and the Internet of Medical Things (IoMT) are becoming more ubiquitous. It uses smart medical devices and cloud computing services, and basic Internet of Things (IoT) technology, to detect key body indicators, monitor health situations, and generate multivariate data to provide just-in-time healthcare services. In this article, we present a novel collaborative disease detection system based on IoMT amalgamated with captured image data. The system can be based on intelligent agents, where every agent explores the interaction between different medical data obtained by smart sensor devices using reinforcement learning as well as targets to detect diseases. The agents then collaborate to make a reliable conclusion about the detected diseases. Intensive experiments were conducted using medical data. The results show the importance of using intelligent agents for disease detection in healthcare decision-making. Moreover, collaboration increases the detection rate, with numerical results showing the superiority of the proposed framework compared with baseline solutions for disease detection.

Automated summary

With the increase in smart medical devices and applications in healthcare settings, the use of IoT and intelligent agents for disease detection and healthcare decision-making has become more important. This article presents a collaborative disease detection system based on IoMT and image data, where intelligent agents explore the medical data obtained from smart sensor devices using reinforcement learning to detect diseases. The results of intensive experiments show the significance of using intelligent agents and collaboration in disease detection, surpassing baseline solutions.