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Using Machine-Learning to Predict Sleep-Disordered Breathing Diagnosis From Medical Comorbidities and Craniofacial Features

Objectives This paper attempts to use machine-learning (ML) algorithms to predict the presence of sleep-disordered breathing (SDB) in a patient based on their body habitus, craniofacial anatomy, and social history. Materials and methods Data from a group of 69 adult patients who attended a dental cl...

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Detalles Bibliográficos
Autores principales: Cokim, Stephen, Ghaly, Joshua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313386/
https://www.ncbi.nlm.nih.gov/pubmed/37398724
http://dx.doi.org/10.7759/cureus.39798