STUDY DESIGN: One case report of proximal tibia fracture in a patient with incomplete spinal cord injury (SCI) associated with robotic treadmill training.
OBJECTIVES: To evaluate how different test set sampling strategies-random selection and balanced sampling-affect the performance of artificial intelligence (AI) models in pediatric wrist fracture detection using radiographs, aiming to highlight the n...
BACKGROUND: It is becoming increasingly important to evaluate the effectiveness of large language models (LLMs) and query-assisted platforms like Google and ChatGPT in providing clinically relevant and accurate information to patient-initiated inquir...
PURPOSE: To identify predictors of a true scaphoid fracture among patients with radial wrist pain following acute trauma, train 5 machine learning (ML) algorithms in predicting scaphoid fracture probability, and design a decision rule to initiate adv...
The deployment of AI in medical imaging, particularly in areas such as fracture detection, represents a transformative advancement in orthopaedic care. AI-driven systems, leveraging deep-learning algorithms, promise to enhance diagnostic accuracy, re...
Percutaneous screw fixation technique in pelvic trauma surgery is an extremely challenging operation that typically requires a trial-and-error insertion process under the guidance of continuous intraoperative X-ray. This process can be simplified by ...
PURPOSE: Artificial Intelligence (AI) has been shown to enhance fracture-detection-accuracy, but the most effective AI-implementation in clinical practice is less well understood. In the current study, four approaches to AI-implementation are evaluat...
PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting to Pediatric Emergency Departments (EDs). These fractures are treated conservatively or surgically depending on deformity severity. Radiographs are t...
The Journal of the American Academy of Orthopaedic Surgeons
Jun 1, 2025
BACKGROUND: Artificial intelligence (AI) technologies have recently exploded in both accessibility and applicability, including in health care. Although studies have demonstrated its ability to adequately answer simple patient issues or multiple-choi...
This retrospective study leverages machine learning to determine the optimal timing for fracture reconstruction surgery in polytrauma patients, focusing on those with concomitant traumatic brain injury. The analysis included 218 patients admitted to ...
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