Almanac — Retrieval-Augmented Language Models for Clinical Medicine
287 Citations•2024•
Cyril Zakka, Rohan Shad, Akash Chaurasia
Almanac, an LLM framework augmented with retrieval capabilities from curated medical resources for medical guideline and treatment recommendations, showed a significant improvement in performance compared with the standard LLMs across axes of factuality, completeness, user preference, and adversarial safety.
Abstract
Our results show the potential for LLMs with access to domain-specific corpora to be effective in clinical decision-making. The findings also underscore the importance of carefully testing LLMs before deployment to mitigate their shortcomings. (Funded by the National Institutes of Health, National Heart, Lung, and Blood Institute.).