Resources

Automated generation of clinically accurate radiology reports can improve patient care. In order to improve automatic report generation, it is helpful to understand what types of errors are common in generated reports. Thus, we introduce the Report …

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports. The dataset contains annotations from 6 board certified radiologists on clinic…

Radiology reports are essential for clinical care but pose challenges for automated processing due to their unstructured nature. Existing datasets like RadGraph-1.0 focus narrowly on chest X-rays (CXR), limiting their applicability. We introduce Rad…

CXRGraph is a dataset of structured radiology reports dataset following the RadGraph format, which has been tailored for the Automatic Radiology Report Generation (ARRG) task. CXRGraph assorts clinical information from full-text radiology reports in…

The Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX) is publicly available and developed similarly to the ReXVal dataset. Just like ReXVal, RadEvalX focuses on radiologist evaluations of errors found in automatically…

RadGraph2 is a dataset of 800 chest radiology reports annotated using a fine-grained entity-relationship schema, which is an expanded version of the previously introduced RadGraph dataset. In contrast with the previous approaches and the original Ra…

RadGraph is a dataset of entities and relations in full-text radiology reports. We designed a novel information extraction (IE) schema to structure clinical information in a radiology report with four entities and three relations. Our train set cons…

We present a radiology question answering dataset, RadQA, with 3074 questions posed against radiology reports and annotated with their corresponding answer spans (resulting in a total of 6148 question-answer evidence pairs) by physicians. The questi…

Generative vision-language models have exciting potential implications for radiology report generation, but unfortunately such models are also known to produce hallucinations and other nonsensical statements. For example, radiology report generation…

Pulmonary embolism (PE) is a leading cause of preventable in-hospital mortality. Advances in diagnosis, risk stratification, and prevention can improve outcomes. Large, publicly available datasets are needed to move research forward but are lacking …