Addressing data accuracy and information integrity in mHealth using ML
Sako, Zaid Zekiria 2019, Addressing data accuracy and information integrity in mHealth using ML, MAppSci thesis, School of Health and Social Development, Deakin University.
The aim of the study was finding a way in which Machine Learning can be applied in mHealth Solutions to detect inaccurate data that can potentially harm patients. The result was an algorithm that classified accurate and inaccurate data.
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.