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Clinical Prediction Models for Sleep Apnea: The Importance of Medical History over Symptoms

STUDY OBJECTIVE: Obstructive sleep apnea (OSA) is a treatable contributor to morbidity and mortality. However, most patients with OSA remain undiagnosed. We used a new machine learning method known as SLIM (Supersparse Linear Integer Models) to test the hypothesis that a diagnostic screening tool ba...

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Publicat a:J Clin Sleep Med
Autors principals: Ustun, Berk, Westover, M. Brandon, Rudin, Cynthia, Bianchi, Matt T.
Format: Artigo
Idioma:Inglês
Publicat: American Academy of Sleep Medicine 2016
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4751423/
https://ncbi.nlm.nih.gov/pubmed/26350602
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5664/jcsm.5476
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