Figure 2: Explainable Risk Prediction and Training.

An overview of our approach. Left: We retrieve evidence snippets from past notes with an LLM for predefined queries posed by a clinician. Then we use our risk prediction model to estimate risk of various diagnoses given each piece of evidence individually, and aggregate these scores. Right: We automatically extract diagnosis ‘labels’ from future reports with an LLM to use to train the risk predictor.