UNLABELLED: Osteoporosis screening should be systematic in the group of over 50-year-old females with a radius fracture. We tested a phantom combined with machine learning model and studied osteoporosis-related variables. This machine learning model ...
UNLABELLED: This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% diagnostic accuracy and significantly faster response times compared to clinicians. The findings highlight the potential for artificial intelligence (A...
UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convoluti...
UNLABELLED: An artificial intelligence-based case-finding strategy has been developed to systematically identify individuals with osteoporosis or at varying risk of fragility fracture. This strategy has the potential to close the critical care gap in...
UNLABELLED: Accessible, accurate information, and readability play crucial role in empowering individuals managing osteoporosis. This study showed that the responses generated by ChatGPT regarding osteoporosis had serious problems with quality and we...
UNLABELLED: We developed a new model for predicting bone mineral density on chest radiographs and externally validated it using images captured at facilities other than the development environment. The model performed well and showed potential for cl...
OBJECTIVE: To conduct a systematic review on the effect of robot-assisted minimally invasive surgery (R-MIS) on the clinical outcomes and complications of patients with osteoporotic vertebral compression fractures (OVCFs).
UNLABELLED: DeepDXA is a deep learning model designed to infer bone mineral density data from plain pelvis X-ray, and it can achieve good predicted value for clinical use.