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Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity Biomedica partnered with Dokkyo Medical University Saitama Medical Center in Japan to complete real-world external validation of its osteoporosis AI model "AIXA Osteo" in Japan, overcoming cross-ethnic imaging and database differences. The findings were published in the European Journal of Radiology, establishing a replicable model for Taiwan's cross-border medical AI export. 5.78MB download
Automated osteoporosis classification and T-score prediction using hip radiographs via deep learning algorithm This study proposed and validated a controllable feature layer of a convolutional neural network (CNN) model with a preprocessing image algorithm to classify osteoporosis and predict T-score on the proximal hip region via simple hip radiographs. 1.22MB download
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