A fully-automatic semi-supervised deep learning model for difficult airway assessment

BACKGROUND: Difficult airway conditions represent a substantial challenge for clinicians. Predicting such conditions is essential for subsequent treatment planning, but the reported diagnostic accuracies are still quite low. To overcome these challenges, we developed a rapid, non-invasive, cost-effe...

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Detalles Bibliográficos
Autores principales: Wang, Guangzhi, Li, Chenxi, Tang, Fudong, Wang, Yangyang, Wu, Su, Zhi, Hui, Zhang, Fan, Wang, Meiyun, Zhang, Jiaqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163620/
https://www.ncbi.nlm.nih.gov/pubmed/37159696
http://dx.doi.org/10.1016/j.heliyon.2023.e15629

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163620/
https://www.ncbi.nlm.nih.gov/pubmed/37159696
http://dx.doi.org/10.1016/j.heliyon.2023.e15629

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