Combined unsupervised-supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea.

doi:10.1038/s41598-021-84003-4

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Article

Combined unsupervised-supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea.

Scientific reports - 24 Feb 2021

Ma Eun-Yeol, Kim Jeong-Whun, Lee Youngmin, Cho Sung-Woo, Kim Heeyoung, Kim Jae Kyoung

Abstract excerpt

Unsupervised clustering models have been widely used for multimetric phenotyping of complex and heterogeneous diseases such as diabetes and obstructive sleep apnea (OSA) to more precisely characterize the disease beyond simplistic conventional diagnosis standards. However, the number of clusters...

Topics

Adult
Cluster Analysis
Comorbidity
Humans
Middle Aged
Phenotype
Polysomnography
Sleep Apnea, Obstructive
Supervised Machine Learning
Unsupervised Machine Learning

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