AIMC Topic: Hip Fractures
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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...
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.
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...
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.
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.
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...
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...
Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.
Annals of medicine
Jun 20, 2024
BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of concentrated red blood cells due to preoperative anemia or surgical blood loss. However, the use of perioperative blood products increases the risk of ad...
Development and validation of an artificial intelligence model for the classification of hip fractures using the AO-OTA framework.
Acta orthopaedica
Jun 18, 2024
BACKGROUND AND PURPOSE: Artificial intelligence (AI) has the potential to aid in the accurate diagnosis of hip fractures and reduce the workload of clinicians. We primarily aimed to develop and validate a convolutional neural network (CNN) for the au...
Incorporating preoperative frailty to assist in early prediction of postoperative pneumonia in elderly patients with hip fractures: an externally validated online interpretable machine learning model.
BMC geriatrics
May 30, 2024
BACKGROUND: This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians.
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