An Intelligent Collaborative Image-Sensing System for Disease Detection
IEEE Sensors Journal
; 23(2):947-954, 2023.
Article
in English
| Scopus | ID: covidwho-2240307
ABSTRACT
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. © 2001-2012 IEEE.
Decision making; Deep learning; Diagnosis; Health care; Intelligent agents; Internet of things; Medical imaging; Multi agent systems; Reinforcement learning; Smart sensors; Collaboration; Communicable disease; Correlation; Disease detection; Medical diagnostic imaging; Medical services; Pandemic; Sensors data; Smart sensor data; COVID-19; multiagent system (MAS)
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
IEEE Sensors Journal
Year:
2023
Document Type:
Article
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