HyTrax: Deep Sequential Modeling of Serial Musculoskeletal Measurements for Fracture Prediction in the Women's Health Initiative with External Evaluation in the Framingham Heart Study

The clinical utility of monitoring longitudinal changes in musculoskeletal trajectories, including bone mineral density (BMD), muscle strength, height, and weight for fracture prediction, remains underutilized, as current gold-standard tools such as the Fracture Risk Assessment Tool (FRAX) rely solely on cross-sectional baseline data. This study aimed to determine whether a deep learning model integrating individualized musculoskeletal trajectories improves fracture prediction accuracy compared to established static benchmarks. We developed the Hybrid Trajectory-Based model (HyTrax), a Transformer-based deep learning model that encodes sequential measurements of hip and spine BMD, grip stren