Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning

STUDY OBJECTIVES: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and increasing costs. Our objective was to optimize this di...

詳細記述

保存先:
書誌詳細
出版年:J Clin Sleep Med
主要な著者: Stretch, Robert, Ryden, Armand, Fung, Constance H., Martires, Joanne, Liu, Stephen, Balasubramanian, Vidhya, Saedi, Babak, Hwang, Dennis, Martin, Jennifer L., Della Penna, Nicolás, Zeidler, Michelle R.
フォーマット: Artigo
言語:Inglês
出版事項: American Academy of Sleep Medicine 2019
主題:
Scientific Investigations
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC6853403/
https://ncbi.nlm.nih.gov/pubmed/31739849
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5664/jcsm.8020
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