Literature-Augmented Clinical Outcome Prediction
Citations Over TimeTop 10% of 2022 papers
Abstract
We present BEEP (Biomedical Evidence-Enhanced Predictions), a novel approach for clinical outcome prediction that retrieves patient-specific medical literature and incorporates it into predictive models. 1 Based on each individual patient's clinical notes, we train language models (LMs) to find relevant papers and fuse them with information from notes to predict outcomes such as in-hospital mortality. We develop methods to retrieve literature based on noisy, information-dense patient notes, and to augment existing outcome prediction models with retrieved papers in a manner that maximizes predictive accuracy. Our approach boosts predictive performance on three important clinical tasks in comparison to strong recent LM baselines, increasing F1 by up to 5 points and precision@Top-K by a large margin of over 25%.
Related Papers
- → Control Method for Electric Fuses with Controllable Fusing(2013)
- IC Fuse Blowing Method(2008)
- Analysis on the Reason of Fuse Melting Wrongly in Circuit and its Fault Excluding(2002)
- → Development of a Self-Destroying Fuse for Rocket Propelled Grenade Munitions(2019)
- → Fuses(1995)