Dynamic Survival Analysis for Early Event Prediction
Hugo Yèche Manuel Burger Dinara Veshchezerova Gunnar Rätsch
This study advances Early Event Prediction (EEP) in healthcare through
Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk
localization into alarm policies to enhance clinical event metrics. By adapting
and evaluating DSA models against traditional EEP benchmarks, our research
demonstrates their ability to match EEP models on a time-step level and
significantly improve event-level metrics through a new alarm prioritization
scheme (up to 11% AuPRC difference). This approach represents a significant
step forward in predictive healthcare, providing a more nuanced and actionable
framework for early event prediction and management.