An artificial neural network model for prediction of hypoxemia during sedation for gastrointestinal endoscopy

OBJECTIVE: This study was designed to assess clinical predictors of hypoxemia and develop an artificial neural network (ANN) model for prediction of hypoxemia during sedation for gastrointestinal endoscopy examination. METHODS: A total of 220 patients were enrolled in this prospective observational...

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Detalles Bibliográficos
Autores principales: Geng, Wujun, Tang, Hongli, Sharma, Apurb, Zhao, Yizhou, Yan, Ye, Hong, Wandong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Clinical Research Reports
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567776/
https://www.ncbi.nlm.nih.gov/pubmed/30913936
http://dx.doi.org/10.1177/0300060519834459

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567776/
https://www.ncbi.nlm.nih.gov/pubmed/30913936
http://dx.doi.org/10.1177/0300060519834459

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