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Automated Osteoporosis Classification and T-Score Prediction
Practical Solutions and Value
- Using a deep learning algorithm, this study aims to classify osteoporosis and predict T-scores on the hip region through simple hip radiographs.
- A dataset of 3460 hip images from 1730 patients was used to train and test the proposed model, which showed a better performance in predicting osteoporosis compared to existing models.
- When combined with variables such as age, body mass index, and sex, the model demonstrated high consistency in T-score prediction compared to dual-energy X-ray absorptiometry (DXA).
- The proposed CNN model may provide high-accuracy identification of osteoporosis and T-score prediction, offering a cost-effective and adaptable solution for population-based osteoporosis screening.
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