Vlada Rozova
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The paper introduces an evidence-augmented machine learning approach to improve self-harm surveillance by analyzing Emergency Department triage notes, achieving high and transferable performance across multiple hospital sites.
This paper investigates why self-harm prediction models struggle to generalize across different hospitals, finding that variations in local lexical expression and feature importance are the primary causes.
Papers
Transferable Self-Harm Surveillance from Emergency Department Triage Notes Using an Evidence-Augmented Machine Learning Approach
Liuliu Chen, Gowri Rajaram, Eleanor Bailey, Katrina Witt +4 more
The paper introduces an evidence-augmented machine learning approach to improve self-harm surveillance by analyzing Emergency Department triage notes, achieving high and transferable performance acros…