Prediagnosis of obstructive sleep apnea via multiclass MTS

Chao Ton Su*, Kun Huang Chen, Li Fei Chen, Pa Chun Wang, Yu Hsiang Hsiao

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

13 引文 斯高帕斯(Scopus)

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.

原文英語
文章編號212498
期刊Computational and Mathematical Methods in Medicine
2012
DOIs
出版狀態已發佈 - 2012
對外發佈

ASJC Scopus subject areas

  • 建模與模擬
  • 一般生物化學,遺傳學和分子生物學
  • 一般免疫學和微生物學
  • 應用數學

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