47 citations · 77 across the 4 of their papers we have counts for
4 papers
MIRIAD: Augmenting LLMs with millions of medical query-response pairs
Qinyue Zheng, Salman Abdullah, Sam Rawal +7
LLMs are bound to transform healthcare with advanced decision support and flexible chat assistants. However, LLMs are prone to generate inaccurate medical content. To ground LLMs i…
GP-VLS: A general-purpose vision language model for surgery
Samuel Schmidgall, Joseph Cho, Cyril Zakka +1
Surgery requires comprehensive medical knowledge, visual assessment skills, and procedural expertise. While recent surgical AI models have focused on solving task-specific problems…
Med-Flamingo: a Multimodal Medical Few-shot Learner
Michael Moor, Qian Huang, Shirley Wu +6
Medicine, by its nature, is a multifaceted domain that requires the synthesis of information across various modalities. Medical generative vision-language models (VLMs) make a firs…
Almanac: Retrieval-Augmented Language Models for Clinical Medicine
Cyril Zakka, Akash Chaurasia, Rohan Shad +11
Large-language models have recently demonstrated impressive zero-shot capabilities in a variety of natural language tasks such as summarization, dialogue generation, and question-a…