Machine learning-based preoperative datamining can predict the therapeutic outcome of sleep surgery in OSA subjects

Increasing recognition of anatomical obstruction has resulted in a large variety of sleep surgeries to improve anatomic collapse of obstructive sleep apnea (OSA) and the prediction of whether sleep surgery will have successful outcome is very important. The aim of this study is to assess a machine l...

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Detalles Bibliográficos
Autores principales: Kim, Jin Youp, Kong, Hyoun-Joong, Kim, Su Hwan, Lee, Sangjun, Kang, Seung Heon, Han, Seung Cheol, Kim, Do Won, Ji, Jeong-Yeon, Kim, Hyun Jik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295249/
https://www.ncbi.nlm.nih.gov/pubmed/34290326
http://dx.doi.org/10.1038/s41598-021-94454-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295249/
https://www.ncbi.nlm.nih.gov/pubmed/34290326
http://dx.doi.org/10.1038/s41598-021-94454-4

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