Machine learning for patient risk stratification for acute respiratory distress syndrome

BACKGROUND: Existing prediction models for acute respiratory distress syndrome (ARDS) require manual chart abstraction and have only fair performance–limiting their suitability for driving clinical interventions. We sought to develop a machine learning approach for the prediction of ARDS that (a) le...

Descripción completa

Detalles Bibliográficos
Autores principales: Zeiberg, Daniel, Prahlad, Tejas, Nallamothu, Brahmajee K., Iwashyna, Theodore J., Wiens, Jenna, Sjoding, Michael W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438573/
https://www.ncbi.nlm.nih.gov/pubmed/30921400
http://dx.doi.org/10.1371/journal.pone.0214465

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438573/
https://www.ncbi.nlm.nih.gov/pubmed/30921400
http://dx.doi.org/10.1371/journal.pone.0214465

Ejemplares similares