An Artificial Neural Network for Nasogastric Tube Position Decision Support

PURPOSE: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed)....

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Detalles Bibliográficos
Autores principales: Drozdov, Ignat, Dixon, Rachael, Szubert, Benjamin, Dunn, Jessica, Green, Darren, Hall, Nicola, Shirandami, Arman, Rosas, Sofia, Grech, Ryan, Puttagunta, Srikanth, Hall, Mark, Lowe, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Radiological Society of North America 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077078/
https://www.ncbi.nlm.nih.gov/pubmed/37035435
http://dx.doi.org/10.1148/ryai.220165

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077078/
https://www.ncbi.nlm.nih.gov/pubmed/37035435
http://dx.doi.org/10.1148/ryai.220165

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