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Found 4 papers, 0 papers with code
Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges
Our method entails tasking an LLM to infer whether a patient has, or is at risk of, a particular condition on the basis of associated notes; if so, we ask the model to summarize the supporting evidence.
CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models
We propose CHiLL (Crafting High-Level Latents), an approach for natural-language specification of features for linear models.
That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data
We compare alignments from a state-of-the-art multimodal (image and text) model for EHR with human annotations that link image regions to sentences.
Query-Focused EHR Summarization to Aid Imaging Diagnosis
We propose and evaluate models that extract relevant text snippets from patient records to provide a rough case summary intended to aid physicians considering one or more diagnoses.
