Preoperative factors predict prolonged length of stay, serious adverse complications, and readmission following operative intervention of proximal humerus fractures a machine learning analysis of a national database

Preoperative factors predict prolonged length of stay, serious adverse complications, and readmission following operative intervention of proximal humerus fractures : a machine learning analysis of a national database

© 2024 The Authors.

Détails bibliographiques
Publié dans:JSES international. - 2020. - 8(2024), 4 vom: 04. Juli, Seite 699-708
Auteur principal: Hornung, Alexander L (Auteur)
Autres auteurs: Rudisill, Samuel S, McCormick, Johnathon R, Streepy, John T, Harkin, William E, Bryson, Noah, Simcock, Xavier, Garrigues, Grant E
Format: Article en ligne
Langue:English
Publié: 2024
Accès à la collection:JSES international
Sujets:Journal Article Arthroplasty Complications Length of stay Machine learning ORIF Outcomes Proximal humerus fracture Readmission
Accès en ligne Volltext