<?xml version="1.0" encoding="UTF-8" ?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-11T13:08:01Z</responseDate><request  verb="GetRecord" metadataPrefix="junii2" identifier="oai:weko.wou.edu.my:00000549">https://weko.wou.edu.my/?action=repository_oaipmh</request><GetRecord><record><header><identifier>oai:weko.wou.edu.my:00000549</identifier><datestamp>2016-11-10T12:06:01Z</datestamp><setSpec>00025</setSpec></header><metadata><junii2 xsi:schemaLocation="http://irdb.nii.ac.jp/oai  http://irdb.nii.ac.jp/oai/junii2-3-1.xsd">
<title lang="en" >Medical expert system for early stage of chronic kidney disease (CKD)</title><language>eng</language><subject>Machine learning algorithm</subject><subject>Medical expert system</subject><subject>Chronic kidney disease</subject><subject>Decision-making ability</subject><URI>http://weko.wou.edu.my/?action=repository_uri&amp;item_id=549</URI><NIItype>Learning Material</NIItype><creator lang="en" >Tan, Choo Jun</creator><creator lang="en" >Teoh, Ping Chow</creator><subject>Expert systems (Computer science)</subject><description>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.</description><type> Electronic </type><type>https://weko.wou.edu.my/?action=repository_action_common_download&amp;item_id=549&amp;item_no=1&amp;attribute_id=15&amp;file_no=1</type><rights>CC BY-NC-SA</rights><description>Penang International Science Fair (SPICE Arena, Penang : 12-13 November 2016)</description><contributor lang="en" >Wawasan Open University</contributor><date>2016-11-09</date></junii2>
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