AIMC Topic: Radius Fractures

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Enhancing pediatric distal radius fracture detection: optimizing YOLOv8 with advanced AI and machine learning techniques.

BMC medical imaging
BACKGROUND: In emergency departments, residents and physicians interpret X-rays to identify fractures, with distal radius fractures being the most common in children. Skilled radiologists typically ensure accurate readings in well-resourced hospitals...

Open-source convolutional neural network to classify distal radial fractures according to the AO/OTA classification on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the perform...

Individual muscle strengths in rehabilitation outcomes of distal radius fracture.

Journal of neuroengineering and rehabilitation
BACKGROUND: Distal radius fractures (DRFs) are common fracture types and elderly patients often struggle to achieve functional recovery, which could be overcome by precise rehabilitation. This study aims to develop an innovative approach for acquirin...

Automatic ultrasound image alignment for diagnosis of pediatric distal forearm fractures.

International journal of computer assisted radiology and surgery
PURPOSE: The study aims to develop an automatic method to align ultrasound images of the distal forearm for diagnosing pediatric fractures. This approach seeks to bypass the reliance on X-rays for fracture diagnosis, thereby minimizing radiation expo...

Machine learning-based prediction of the necessity for the surgical treatment of distal radius fractures.

Journal of orthopaedic surgery and research
BACKGROUND: Treatments for distal radius fractures (DRFs) are determined by various factors. Therefore, quantitative or qualitative tools have been introduced to assist in deciding the treatment approach. This study aimed to develop a machine learnin...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

Orthopaedic surgery
OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Studies have shown that in emergency settings, the misdiagnosis rate of hand/wrist fractures can reach ...

The Role of 3D technology in corrective osteotomy for forearm malunion.

The Journal of hand surgery, European volume
Forearm malunion affects upper limb function, impairing rotation, grip strength, and dexterity. Traditional osteotomies, based on two-dimensional imaging and intraoperative adjustments, may fail to address the intricate three-dimensional aspects of f...

An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Distal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures....

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

Journal of orthopaedic surgery and research
PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there's only scarce evidence for measurable value in terms of patient outcomes, clinical ...