Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40858
Title: Machine learning analysis of multiparameter home telecare clinical measurement data for patient health stratification
Authors: Mohd Hanafi, Mat Som
Keywords: Home telecare
Medical decision support system (DSS)
Machine learning analysis
Patient data
Issue Date: Jul-2008
Publisher: University of New South Wales
Abstract: A medical decision support system (DSS) is designed to assist clinician in monitoring patient’s health by the means of providing reminders, advice as well as interpretation. This system is good enough in the sense of monitoring patient’s health and improves the early prevention by the means of providing ‘just-in-time’ notifications for the best action to be taken. In Biomedical System Laboratory (BSL) of UNSW, there is a system as such described that provides information on the patient’s conditions based on the risk they may have by analyzing the data entered in the database. But there is a need to improve current system to increase their performance. Score generated by the DSS is compared with the journal on patient’s conditions entered manually by medical personnel. The objective is to see the reliability of the score generated by the DSS. Unfortunately, due to some problems on the data, the outcome of this study can’t be used for reference. However, the method used can be repeated but with a better database storing the patient’s information.
URI: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/40858
Appears in Collections:School of Mechatronic Engineering (Theses)

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