Predict depression risk before it manifests
Our model, a tuned gradient-boosted-trees (XGBoost) pipeline built on longitudinal data from The Maastricht Study (2010–2020 baseline), estimates the ~4-year risk of clinically relevant depressive symptoms (PHQ-9 ≥ 10) from wearable-derived sleep and activity metrics, plus clinical and sociodemographic covariates.
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Low-latency scoring
FastAPI + XGBoost ‘hist’ for fast, production-style inference.
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Privacy-first
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Transparent metrics
AUROC 0.71 · AUPRC 0.29 on a hold-out test set of 2,789 records (train = 11,153).