Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation.

Oliver, Matthieu; Renou, Amélie; Allou, Nicolas; Moscatelli, Lucas; Ferdynus, Cyril; Allyn, Jerôme

Oliver, Matthieu; Renou, Amélie; Allou, Nicolas; Moscatelli, Lucas; Ferdynus, Cyril; Allyn, Jerôme.

Afiliación

Oliver M; Methodological Support Unit, Reunion University Hospital, Saint-Denis, France. matthieu.oliver@chu-reunion.fr.
Renou A; Clinical Informatics Department, Reunion University Hospital, Saint-Denis, France. matthieu.oliver@chu-reunion.fr.
Allou N; Intensive Care Unit, Reunion University Hospital, Saint-Denis, France.
Moscatelli L; Methodological Support Unit, Reunion University Hospital, Saint-Denis, France.
Ferdynus C; Intensive Care Unit, Reunion University Hospital, Saint-Denis, France.
Allyn J; Clinical Informatics Department, Reunion University Hospital, Saint-Denis, France.

Crit Care ; 27(1): 40, 2023 01 25.

Article en En | MEDLINE | ID: mdl-36698191

Asunto(s)

Aprendizaje Profundo; Humanos; Tráquea; Intubación Intratraqueal/métodos; Radiografía; Unidades de Cuidados Intensivos

Palabras clave

Chest radiograph; Deep learning; Image processing; Intensive care unit; RetinaNet

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Crit Care Año: 2023 Tipo del documento: Article País de afiliación: Francia

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