Machine learning-based preoperative datamining can predict the therapeutic outcome of sleep surgery in OSA subjects
Abstract 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...
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Autores principales: | Jin Youp Kim, Hyoun-Joong Kong, Su Hwan Kim, Sangjun Lee, Seung Heon Kang, Seung Cheol Han, Do Won Kim, Jeong-Yeon Ji, Hyun Jik Kim |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/7739f359acd748e29325a534916a45ee |
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