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.

Bibliographische Detailangaben
Veröffentlicht in:JSES international. - 2020. - 8(2024), 4 vom: 04. Juli, Seite 699-708
1. Verfasser: Hornung, Alexander L (VerfasserIn)
Weitere Verfasser: Rudisill, Samuel S, McCormick, Johnathon R, Streepy, John T, Harkin, William E, Bryson, Noah, Simcock, Xavier, Garrigues, Grant E
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:JSES international
Schlagworte:Journal Article Arthroplasty Complications Length of stay Machine learning ORIF Outcomes Proximal humerus fracture Readmission
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