RadGraph-XL
收藏DataCite Commons2026-04-30 更新2026-05-05 收录
下载链接：
https://stanford.redivis.com/datasets/4frr-fgm89x6t8?v=1.0
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资源简介：
RadGraph-XL: A Large-Scale Expert-Annotated Dataset for Entity and Relation Extraction from Radiology Reports
RadGraph-XL is a large-scale expert-annotated dataset of 2,300 radiology reports sourced from MIMIC-CXR and Stanford Health Care, spanning chest CT, abdomen/pelvis CT, brain MRI, and chest X-ray. Reports were curated through targeted sampling to maximize clinical and semantic diversity, using condition coverage, clustering with sentence embeddings, and length stratification. Each report was double-annotated by board-certified radiologists with entities (anatomy, observations, measurements) and relations (modify, located at, suggestive of), resulting in ~226k entities and ~180k relations. A post-processing pipeline added over 3k measurement entities, supporting quantitative analysis. Inter-annotator agreement was ≥50%, with adjudication resolving disagreements.
The dataset is released in structured JSON format, split into training, validation, and test sets, and includes pretrained models and tools for entity–relation extraction.
RadGraph-XL sets a benchmark for clinical NLP, enabling research on structured information extraction, measurement understanding, and cross-modality generalization.
提供机构：
Redivis
创建时间：
2026-04-23
