Fusion of X-Ray Images and Clinical Data for a Multimodal Deep Learning Prediction Model of Osteoporosis: Algorithm Development and Validation Study

While the multimodal model that fuses chest X-ray images and clinical data demonstrated superior performance compared to unimodal models and traditional methods, this study has several limitations. The dataset size may not be sufficient to capture the full diversity of the population. The retrospective nature of the study may introduce selection bias, and the lack of external validation limits the generalizability of the findings. Future studies should address these limitations by incorporating larger, more diverse datasets and conducting rigorous external validation to further establish the model's clinical use.