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An intelligent collaborative image-sensing system for disease detection

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.
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Category

Academic article

Language

English

Author(s)

  • Youcef Djenouri
  • Asma Belhadi
  • Anis Yazidi
  • Gautam Srivastava
  • Pushpita Chatterjee
  • Jerry Chun-Wei Lin

Affiliation

  • SINTEF Digital / Mathematics and Cybernetics
  • Kristiania University of Applied Sciences
  • Norwegian University of Science and Technology
  • Oslo University Hospital
  • Western Norway University of Applied Sciences
  • OsloMet - Oslo Metropolitan University
  • China Medical University
  • Lebanese American University
  • Brandon University
  • Tennessee State University

Year

2023

Published in

IEEE Sensors Journal

ISSN

1530-437X

Volume

23

Issue

2

Page(s)

947 - 954

View this publication at Norwegian Research Information Repository