4 citations · 7 across the 10 of their papers we have counts for
11 papers
The RSNA Intracranial Aneurysm (RSNA-ICA) Dataset
Maria Correia de Verdier, Rachit Saluja, Jason Sho +37
Intracranial aneurysm rupture is associated with substantial morbidity and mortality, yet aneurysm detection remains challenging, particularly for small lesions and on routine non-…
Reinforcement Learning Improves LLM Accuracy and Reasoning in Disease Classification from Radiology Reports
Yishu Wei, Yi Lin, Adam Flanders +2
Accurate disease classification from radiology reports is essential for many applications. While supervised fine-tuning (SFT) of lightweight LLMs improves accuracy, it can degrade…
CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification
Hexin Dong, Yi Lin, Pengyu Zhou +25
Chest X-ray (CXR) interpretation is hindered by the long-tailed distribution of pathologies and the open-world nature of clinical environments. Existing benchmarks often rely on cl…
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…
A Multi-agent Large Language Model Framework to Automatically Assess Performance of a Clinical AI Triage Tool
Adam E. Flanders, Yifan Peng, Luciano Prevedello +6
Purpose: The purpose of this study was to determine if an ensemble of multiple LLM agents could be used collectively to provide a more reliable assessment of a pixel-based AI triag…
The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset
Tyler J. Richards, Adam E. Flanders, Errol Colak +33
The Radiological Society of North America (RSNA) Lumbar Degenerative Imaging Spine Classification (LumbarDISC) dataset is the largest publicly available dataset of adult MRI lumbar…
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…
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
Jeffrey D. Rudie, Hui-Ming Lin, Robyn L. Ball +37
The RSNA Abdominal Traumatic Injury CT (RATIC) dataset is the largest publicly available collection of adult abdominal CT studies annotated for traumatic injuries. This dataset inc…
Evaluating GPT-4 with Vision on Detection of Radiological Findings on Chest Radiographs
Yiliang Zhou, Hanley Ong, Patrick Kennedy +6
The study examines the application of GPT-4V, a multi-modal large language model equipped with visual recognition, in detecting radiological findings from a set of 100 chest radiog…