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Hip Fractures

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Machine learning-based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study.

BMC musculoskeletal disorders 40340665
PURPOSE: To evaluate machine learning-based survival model roles in predicting rehospitalization after hip fractures to improve reduce the burden on the healthcare system.
Aged Aged, 80 and over Female Hip Fractures Humans Kaplan-Meier Estimate Machine Learning Male Patient Readmission Retrospective Studies Risk Assessment Support Vector Machine
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All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.

Clinical interventions in aging 40357343
INTRODUCTION: The aim of this study was to identify the influencing factors for all-cause mortality in elderly patients with intertrochanteric and femoral neck fractures and to construct predictive models.
Aged Aged, 80 and over Female Femoral Neck Fractures Hip Fractures Humans Machine Learning Male Nomograms Proportional Hazards Models Retrospective Studies Risk Assessment Risk Factors
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Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

Clinical interventions in aging 40034472
BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative pneumonia due to their frailty and the presence of multiple comorbidities. This study aims to establi...
Aged, 80 and over Algorithms China Female Hip Fractures Humans Incidence Logistic Models Machine Learning Male Neural Networks, Computer Pneumonia Postoperative Complications Risk Assessment Risk Factors Support Vector Machine
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Patch-based feature mapping with generative adversarial networks for auxiliary hip fracture detection.

Computers in biology and medicine 39793347
BACKGROUND: Hip fractures are a significant public health issue, particularly among the elderly population. Pelvic radiographs (PXRs) play a crucial role in diagnosing hip fractures and are commonly used for their evaluation. Previous research has de...
Aged Algorithms Female Generative Adversarial Networks Hip Fractures Humans Male Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted
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Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

Academic radiology 39904664
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine CT to predict hip fragility fracture using machine learning methods.
Aged Aged, 80 and over Female Hip Fractures Humans Machine Learning Male Middle Aged Radiographic Image Interpretation, Computer-Assisted Radiomics Risk Assessment Risk Factors Tomography, X-Ray Computed
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Deep learning for automated hip fracture detection and classification : achieving superior accuracy.

The bone & joint journal 39889758
AIMS: The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy.
Aged Aged, 80 and over Deep Learning Female Hip Fractures Humans Male Neural Networks, Computer Radiography Retrospective Studies Sensitivity and Specificity
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Development and validation of explainable machine learning models for female hip osteoporosis using electronic health records.

International journal of medical informatics 40132236
BACKGROUND: Hip fractures are associated with reduced mobility, and higher morbidity, mortality, and healthcare costs. Approximately 90% of hip fractures in the elderly are associated with osteoporosis, making it particularly important to screen the ...
Absorptiometry, Photon Aged Algorithms Bone Density Electronic Health Records Female Hip Fractures Humans Machine Learning Middle Aged Osteoporosis Retrospective Studies
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Elucidating predictors of preoperative acute heart failure in older people with hip fractures through machine learning and SHAP analysis: a retrospective cohort study.

BMC geriatrics 40269712
BACKGROUND: Acute heart failure (AHF) has become a significant challenge in older people with hip fractures. Timely identification and assessment of preoperative AHF have become key factors in reducing surgical risks and improving outcomes.
Acute Disease Aged Aged, 80 and over Cohort Studies Female Heart Failure Hip Fractures Humans Machine Learning Male Preoperative Period Retrospective Studies Risk Assessment Risk Factors
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Screening risk factors for the occurrence of wedge effects in intramedullary nail fixation for intertrochanteric fractures in older people via machine learning and constructing a prediction model: a retrospective study.

BMC musculoskeletal disorders 40264104
PURPOSE: The wedge effect (V-effect) is a common complication in intramedullary nailing surgery for intertrochanteric fractures and can significantly affect postoperative outcomes. The purpose of this study was to screen risk factors for the intraope...
Aged Aged, 80 and over Bone Nails China Female Fracture Fixation, Intramedullary Hip Fractures Humans Intraoperative Complications Machine Learning Male Middle Aged Postoperative Complications Retrospective Studies Risk Assessment Risk Factors
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Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Scientific reports 40240511
Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increased risk of developing preoperative deep vein thrombosis (DVT). DVT not only heightens surgical risk...
Aged Aged, 80 and over Female Hip Fractures Humans Hypertension Incidence Logistic Models Machine Learning Male Nomograms Preoperative Period Retrospective Studies Risk Assessment Risk Factors ROC Curve Venous Thrombosis
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