Predicting outcomes after trauma: Prognostic model development based on admission features through machine learning

In an overcrowded emergency department (ED), trauma surgeons and emergency physicians need an accurate prognostic predictor for critical decision-making involving patients with severe trauma. We aimed to develope a machine learning-based early prognostic model based on admission features and initial...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Kuo-Chang, Lin, Tzu-Chieh, Chiang, Hsiu-Fen, Horng, Gwo-Jiun, Hsu, Chien-Chin, Wu, Nan-Chun, Su, Hsiu-Chen, Chen, Kuo-Tai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
7100
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8663914/
https://www.ncbi.nlm.nih.gov/pubmed/34889225
http://dx.doi.org/10.1097/MD.0000000000027753

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8663914/
https://www.ncbi.nlm.nih.gov/pubmed/34889225
http://dx.doi.org/10.1097/MD.0000000000027753

Ejemplares similares