Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study

PURPOSE: In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial intelligence (AI), could be used to detect patien...

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Detalles Bibliográficos
Autores principales: Tsuiki, Satoru, Nagaoka, Takuya, Fukuda, Tatsuya, Sakamoto, Yuki, Almeida, Fernanda R., Nakayama, Hideaki, Inoue, Yuichi, Enno, Hiroki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Dentistry • Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590647/
https://www.ncbi.nlm.nih.gov/pubmed/33559004
http://dx.doi.org/10.1007/s11325-021-02301-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590647/
https://www.ncbi.nlm.nih.gov/pubmed/33559004
http://dx.doi.org/10.1007/s11325-021-02301-7

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