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dc.contributor.authorDjenouri, Youcef
dc.contributor.authorBelhadi, Asma
dc.contributor.authorYazidi, Anis
dc.contributor.authorSrivastava, Gautam
dc.contributor.authorChatterjee, Pushpita
dc.contributor.authorLin, Jerry Chun-Wei
dc.date.accessioned2023-10-19T07:43:35Z
dc.date.available2023-10-19T07:43:35Z
dc.date.created2023-02-28T11:55:09Z
dc.date.issued2023
dc.identifier.citationIEEE Sensors Journal. 2023, 23 (2), 947-954.en_US
dc.identifier.issn1530-437X
dc.identifier.urihttps://hdl.handle.net/11250/3097443
dc.description.abstractWith 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.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titleAn intelligent collaborative image-sensing system for disease detectionen_US
dc.title.alternativeAn intelligent collaborative image-sensing system for disease detectionen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber947-954en_US
dc.source.volume23en_US
dc.source.journalIEEE Sensors Journalen_US
dc.source.issue2en_US
dc.identifier.doi10.1109/JSEN.2022.3202437
dc.identifier.cristin2130025
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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