Prediction Models for Obstructive Sleep Apnea in Korean Adults Using Machine Learning Techniques

This study aimed to investigate the applicability of machine learning to predict obstructive sleep apnea (OSA) among individuals with suspected OSA in South Korea. A total of 92 clinical variables for OSA were collected from 279 South Koreans (OSA, n = 213; no OSA, n = 66), from which seven major cl...

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Detalles Bibliográficos
Autores principales: Kim, Young Jae, Jeon, Ji Soo, Cho, Seo-Eun, Kim, Kwang Gi, Kang, Seung-Gul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066462/
https://www.ncbi.nlm.nih.gov/pubmed/33808100
http://dx.doi.org/10.3390/diagnostics11040612

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066462/
https://www.ncbi.nlm.nih.gov/pubmed/33808100
http://dx.doi.org/10.3390/diagnostics11040612

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