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標題:Prediagnosis of Obstructive Sleep Apnea via Multiclass MTS
學年100
學期1
出版(發表)日期2012/01/09
作品名稱Prediagnosis of Obstructive Sleep Apnea via Multiclass MTS
作品名稱(其他語言)
著者C.-T. Su; K.-H. Chen; L.-F. Chen; P.-C. Wang; Y.-H. Hsiao
單位
出版者
著錄名稱、卷期、頁數Computational and Mathematical Methods in Medicine 2012, 212498(8pages)
摘要Obstructive sleep apnea (OSA) has become an important public health concern. Polysomnography (PSG) is traditionally considered an established and effective diagnostic tool providing information on the severity of OSA and the degree of sleep fragmentation. However, the numerous steps in the PSG test to diagnose OSA are costly and time consuming. This study aimed to apply the multiclass Mahalanobis-Taguchi system (MMTS) based on anthropometric information and questionnaire data to predict OSA. Implementation results showed that MMTS had an accuracy of 84.38% on the OSA prediction and achieved better performance compared to other approaches such as logistic regression, neural networks, support vector machine, C4.5 decision tree, and rough set. Therefore, MMTS can assist doctors in prediagnosis of OSA before running the PSG test, thereby enabling the more effective use of medical resources.
關鍵字
語言英文(美國)
ISSN1748-670X;1748-6718
期刊性質國外
收錄於SCI;
產學合作
通訊作者C.-T. Su
審稿制度
國別美國
公開徵稿
出版型式,電子版,紙本
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