AIMC Topic: Hip Fractures

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Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

Clinical interventions in aging Feb 27, 2025
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...
Hip Fractures Male Risk Assessment Postoperative Complications China Incidence Logistic Models Support Vector Machine Pneumonia Algorithms Female Risk Factors Aged, 80 and over Humans Neural Networks, Computer Machine Learning
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Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

Academic radiology Feb 3, 2025
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.
Tomography, X-Ray Computed Female Risk Factors Aged Humans Machine Learning Risk Assessment Radiographic Image Interpretation, Computer-Assisted Hip Fractures Aged, 80 and over Radiomics Male Middle Aged
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Deep learning for automated hip fracture detection and classification : achieving superior accuracy.

The bone & joint journal Feb 1, 2025
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.
Radiography Hip Fractures Neural Networks, Computer Retrospective Studies Female Aged Aged, 80 and over Humans Sensitivity and Specificity Male Deep Learning
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Patch-based feature mapping with generative adversarial networks for auxiliary hip fracture detection.

Computers in biology and medicine Jan 10, 2025
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...
Female Aged Male Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms Hip Fractures Generative Adversarial Networks
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An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.

BMC anesthesiology Dec 19, 2024
AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) transfusion during hip fracture surgery.
Erythrocyte Transfusion Retrospective Studies Female Aged Aged, 80 and over Humans Supervised Machine Learning Algorithms Anemia Male Hip Fractures Middle Aged
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Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.

The Journal of the American Academy of Orthopaedic Surgeons Nov 19, 2024
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study was to determine the reliability of assessing surgical risk after hip fracture through machine learnin...
Algorithms Female Reproducibility of Results Aged Humans Machine Learning Comorbidity Length of Stay Predictive Value of Tests Aged, 80 and over Patient Readmission Male Hip Fractures Risk Assessment Postoperative Complications
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Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BMC medical informatics and decision making Nov 6, 2024
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.
Humans Machine Learning Retrospective Studies Female Aged Aged, 80 and over Male Risk Assessment Heart Failure Logistic Models Hip Fractures Hypertension Acute Disease
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Interpretable prediction of acute ischemic stroke after hip fracture in patients 65 years and older based on machine learning and SHAP.

Archives of gerontology and geriatrics Sep 19, 2024
BACKGROUND: Hip fracture and acute ischemic stroke (AIS) are prevalent conditions among the older population. The prognosis for older patients who experience AIS subsequent to hip fracture is frequently unfavorable.
Male Humans Nomograms Support Vector Machine Hip Fractures Female Ischemic Stroke Propensity Score Risk Factors Aged Aged, 80 and over Machine Learning Prognosis
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Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference.

Diagnostic and interventional imaging Sep 19, 2024
PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radi...
Reference Standards Pelvic Bones Fractures, Bone Radiologists Retrospective Studies Hip Fractures Tomography, X-Ray Computed Aged, 80 and over Female Humans Adult Aged Artificial Intelligence Male Middle Aged
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Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a national cohort study of 52 707 cases.

International journal of surgery (London, England) Aug 1, 2024
BACKGROUND: In-hospital mortality following hip fractures is a significant concern, and accurate prediction of this outcome is crucial for appropriate clinical management. Nonetheless, there is a lack of effective prediction tools in clinical practic...
Cohort Studies Aged Hospital Mortality Humans Aged, 80 and over Logistic Models Artificial Intelligence Hip Fractures Male Internet Machine Learning Risk Assessment Female
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