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<rdf:Description rdf:about="http://weko.wou.edu.my/?action=repository_uri&amp;item_id=549">
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	<swrc:title xml:lang="en">Medical expert system for early stage of chronic kidney disease (CKD)</swrc:title>
	<dc:language>en</dc:language>
	<swrc:keyword xml:lang="en">Machine learning algorithm</swrc:keyword>
	<swrc:keyword xml:lang="en">Medical expert system</swrc:keyword>
	<swrc:keyword xml:lang="en">Chronic kidney disease</swrc:keyword>
	<swrc:keyword xml:lang="en">Decision-making ability</swrc:keyword>
	<swrc:editor xml:lang="en">Choo Jun Tan</swrc:editor>
	<swrc:editor xml:lang="en">Ping Chow Teoh</swrc:editor>
	<dc:subject xml:lang="en">Expert systems (Computer science)</dc:subject>
	<swrc:abstract xml:lang="en">WOU Medical Expert System (MES) is a computer system that emulates the decision-making ability of a medical expert. MES is designed to tackle the complex problem of Chronic Kidney Disease (CKD). It adopts Machine-Learning (ML) algorithm, which has the ability to learn without being explicitly programmed in application level. ML evolved from the study of pattern recognition and computational learning theory in artificial intelligence. ML aids MES to learn from the given historical data and make predictions based on incoming new data from laboratory results. Reasoning method with ML was performed on the selected known facts that caused CKD. Experiment with a sample of 400 patients in an early diagnosis stage from a designated hospital was conducted. MES has recorded an accuracy rate of 99.25% in the 10-fold Cross Validation based knowledge updating processes.</swrc:abstract>
	<swrc:type xml:lang="en"> Electronic </swrc:type>
	<swrc:abstract xml:lang="en">Penang International Science Fair (SPICE Arena, Penang : 12-13 November 2016)</swrc:abstract>
	<dc:contributor xml:lang="en">Wawasan Open University</dc:contributor>
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