ロード中...
Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample
STUDY OBJECTIVES: Polysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction model to identify patients with high probability o...
保存先:
| 出版年: | Sleep |
|---|---|
| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Oxford University Press
2020
|
| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7355399/ https://ncbi.nlm.nih.gov/pubmed/31917446 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/sleep/zsz295 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|