4 citations · 5 across the 4 of their papers we have counts for
4 papers
RSNA Large Language Model Benchmark Dataset for Chest Radiographs of Cardiothoracic Disease: Radiologist Evaluation and Validation Enhanced by AI Labels (REVEAL-CXR)
Yishu Wei, Adam E. Flanders, Errol Colak +35
Multimodal large language models have demonstrated comparable performance to that of radiology trainees on multiple-choice board-style exams. However, to develop clinically useful…
CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray
Mingquan Lin, Gregory Holste, Song Wang +30
The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges in open long-tailed lung disease…
Generative Large Language Models Trained for Detecting Errors in Radiology Reports
Cong Sun, Kurt Teichman, Yiliang Zhou +8
In this retrospective study, a dataset was constructed with two parts. The first part included 1,656 synthetic chest radiology reports generated by GPT-4 using specified prompts, w…
Enhancing disease detection in radiology reports through fine-tuning lightweight LLM on weak labels
Yishu Wei, Xindi Wang, Hanley Ong +4
Despite significant progress in applying large language models (LLMs) to the medical domain, several limitations still prevent them from practical applications. Among these are the…