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dc.contributor.authorEffiok, Emmanuel
dc.contributor.authorLiu, Enjie
dc.contributor.authorYu, Hong Qing
dc.contributor.authorHitchcock, Jonathan James
dc.date.accessioned2020-08-11T09:43:50Z
dc.date.available2020-08-11T09:43:50Z
dc.date.issued2015-12-28
dc.identifier.citationEffiok E, Liu E, Yu H, Hitchcock J (2015) 'A prostate cancer care process example of using data from internet of things', IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing - Liverpool, Institute of Electrical and Electronics Engineers Inc..en_US
dc.identifier.isbn9781509001545
dc.identifier.doi10.1109/CIT/IUCC/DASC/PICOM.2015.340
dc.identifier.urihttp://hdl.handle.net/10547/624358
dc.description.abstractIn this research, we use prostate cancer as an example to describe the idea of using Internet of Things (IoT) technology as part of the care process for chronic diseases. IoT provides ways to monitor and collect critical risk elements data that relate to the causes and development of the disease and its comorbidities, on a real time basis over a long period of time by sensing and communication capacity. The risk models and their evidences are gathered from the literature, and they will be semantically described to support the knowledge to be used by other applications. The personal data collected by IoT devices combined with risk models will provide individual risk prediction. The prediction can be used by patients in self-managing their chronic disease, and also help medical professionals to take in-sight look into the progression of the disease for the individual patient, in order to prescribe the best suitable care plan and treatment.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.urlhttps://ieeexplore.ieee.org/document/7363386/en_US
dc.subjectsemantic representationen_US
dc.subjectIoTen_US
dc.subjectInternet of Thingsen_US
dc.subjectdisease risk predictive modellingen_US
dc.titleA prostate cancer care process example of using data from internet of thingsen_US
dc.typeConference papers, meetings and proceedingsen_US
dc.contributor.departmentUniversity of Bedfordshireen_US
dc.date.updated2020-08-11T09:40:54Z
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