Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/1527
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dc.contributor.authorWickramasinghe, Nilmini-
dc.contributor.otherSako, Zaid-
dc.contributor.otherKarpathiou, Vass-
dc.contributor.otherAdibi, Sasan-
dc.date.accessioned2018-10-17T22:33:20Z-
dc.date.available2018-10-17T22:33:20Z-
dc.date.issued2017-
dc.identifier.isbn9781522509202en_US
dc.identifier.urihttp://hdl.handle.net/11434/1527-
dc.description.abstractWith the plethora of mHealth solutions developed being digital, this necessitates the need for accurate data and information integrity. Lack of data accuracy and information integrity in mHealth can cause serious harm to patients and limit the benefits of such promising technology. Thus, this exploratory study investigates data accuracy and information integrity in mHealth by examining a mobile health solution for diabetes, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information.en_US
dc.publisherIGI Globalen_US
dc.subjectmHealthen_US
dc.subjectInformation Integrityen_US
dc.subjectData Integrityen_US
dc.subjectData Accuracyen_US
dc.subjectChair of Health Informatics Management, Epworth HealthCare, Victoria, Australiaen_US
dc.titleData accuracy considerations with mHealth.en_US
dc.typeChapteren_US
dc.identifier.doi10.4018/978-1-5225-0920-2.ch001en_US
dc.description.affiliatesHealth Informaticsen_US
dc.description.affiliatesRMIT University, Melbourne, Victoria, Australiaen_US
dc.description.affiliatesDeakin University, Melbourne, Victoria, Australiaen_US
dc.type.contenttypeTexten_US
dc.title.bookHandbook of Research on Healthcare Administration and Managementen_US
Appears in Collections:Health Informatics

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