OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radio...
PURPOSE: Computer vision and artificial intelligence (AI) offer the opportunity to rapidly and accurately interpret standardized x-rays. We trained and validated a machine learning tool that identified key reference points and determined glenoid retr...
OBJECTIVE: Our study aims to develop a deep learning-based Ankylosing Spondylitis (AS) diagnostic model that achieves human expert-level performance using only a minimal amount of labeled samples for training, in regions with limited access to expert...
BACKGROUND: Predicting the progression of hip osteoarthritis (OA) remains challenging, and no reliable predictive method has been established. This study aimed to develop an artificial intelligence (AI) model to predict hip OA progression via plain r...
Humans have been shown to have biases when reading medical images, raising questions about whether humans are uniform in their disease gradings. Artificial intelligence (AI) tools trained on human-labeled data may have inherent human non-uniformity. ...
PURPOSE: Osteoporosis, affecting over 200 million individuals, often remains unrecognized and untreated, increasing the risk of fractures in older adults. Osteoporosis is typically diagnosed with bone mineral density (BMD) measured by dual-energy X-r...
AIMS: The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular ...
PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatment and unfavorable prognosis. Here, we developed a fully automated deep learning model to detect and ...
BACKGROUND: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardwar...
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