Clinical NLP

New! Memorize and Rank: Enabling Large Language Models for Medical Event Prediction

We introduce Mera, a clinical event prediction model that bridges pertaining natural language knowledge with medical code. We apply contrastive learning on a predicted ranking list for task-specialized optimization. With concept memorization through fine-tuning, we equip the LLM with an in-depth understanding to recall the natural language definitions for medical code during inference.

Mingyu Derek Ma, Yijia Xiao, Anthony Cuturrufo, Xiaoxuan Wang, Wei Wang

DICE: Data-Efficient Clinical Event Extraction with Generative Models

We introduce DICE, a robust and data-efficient generative model for clinical event extraction, which specializes in clinical mention identification, and MACCROBAT-EE, the first clinical event extraction dataset with event argument annotation.

Mingyu Derek Ma, Alexander K. Taylor, Wei Wang, Nanyun Peng