Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Length of postoperative stay prediction in elderly patients with hip fractures based on machine learning
0
Zitationen
6
Autoren
2026
Jahr
Abstract
The BP-NN model, enhanced by multimethod feature selection, rigorous parameter tuning, and SHAP based interpretability, provides early and accurate LOPS prediction for elderly hip fracture patients. It can be used as a tool to assist in clinical decision-making, resource planning, and discharge preparation, without increasing the clinical burden. Future external validation across multiple centers is needed to confirm generalizability.
Ähnliche Arbeiten
Guidance for conducting systematic scoping reviews
2015 · 7.161 Zit.
An estimate of the worldwide prevalence and disability associated with osteoporotic fractures
2006 · 4.596 Zit.
Clinician’s Guide to Prevention and Treatment of Osteoporosis
2014 · 4.024 Zit.
Incidence and Economic Burden of Osteoporosis-Related Fractures in the United States, 2005–2025
2006 · 3.996 Zit.
Guidelines for the Provision and Assessment of Nutrition Support Therapy in the Adult Critically Ill Patient
2016 · 3.847 Zit.