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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cureus
2023
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| 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 |