7 citations · 7 across the 2 of their papers we have counts for
4 papers · 1 filter
Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights
Hyunjae Kim, Jiwoong Sohn, Aidan Gilson +24
Large language models (LLMs) are transforming the landscape of medicine, yet two fundamental challenges persist: keeping up with rapidly evolving medical knowledge and providing ve…
Humans and Large Language Models in Clinical Decision Support: A Study with Medical Calculators
Nicholas Wan, Qiao Jin, Joey Chan +8
Although large language models (LLMs) have been assessed for general medical knowledge using licensing exams, their ability to support clinical decision-making, such as selecting m…
LEME: Open Large Language Models for Ophthalmology with Advanced Reasoning and Clinical Validation
Hyunjae Kim, Xuguang Ai, Sahana Srinivasan +27
The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinica…
Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology
Aidan Gilson, Xuguang Ai, Thilaka Arunachalam +19
Despite the potential of Large Language Models (LLMs) in medicine, they may generate responses lacking supporting evidence or based on hallucinated evidence. While Retrieval Augmen…