Three-stage evidence-augmented ML model detects self-harm in ED triage notes at AUPRC ~0.88, transfers across sites without retraining, and identifies primary method at 95% accuracy.
Establishing a self-harm surveillance register to improve care in a general hospital.British Journal of Mental Health Nursing4, 20–25 (2015)
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Transferable Self-Harm Surveillance from Emergency Department Triage Notes Using an Evidence-Augmented Machine Learning Approach
Three-stage evidence-augmented ML model detects self-harm in ED triage notes at AUPRC ~0.88, transfers across sites without retraining, and identifies primary method at 95% accuracy.