RadGraph: CheXpert Results

RadGraph is a dataset of entities and relations in full-text chest X-ray radiology reports based on a novel information extraction schema designed to structure radiology reports. Our paper (accepted to the NeurIPS 2021 Track on Datasets and Benchmarks):https://arxiv.org/abs/2106.14463 Here, we release the subset of the RadGraph dataset corresponding to CheXpert reports, which include RadGraph annotations for the CheXpert test set (test.json) and the CheXpert inference set (CheXpert_graphs.json). - test.json contains two independent sets of board-certified radiologist annotations for 50 deidentified CheXpert reports (1,473 entities and 1,106 relations) - CheXpert_graphs.json contains annotations automatically generated by a deep learning model called the RadGraph Benchmark for 500 deidentified CheXpert reports (13,783 entities and 9,908 relations) with mappings to the associated chest radiographs Documentation for the CheXpert_test.json (same as test.json) and CheXpert_graphs.json files, along with the full RadGraph dataset, can be accessed at the following link:https://doi.org/10.13026/hm87-5p47.

RadGraph（RadGraph）是一款基于全新信息抽取模式构建的、面向全文字胸片放射学报告的实体与关系数据集，旨在实现放射学报告的结构化。本论文已被NeurIPS 2021数据集与基准赛道收录：https://arxiv.org/abs/2106.14463。本次我们发布RadGraph数据集中对应CheXpert报告的子集，其中包含针对CheXpert测试集（test.json）与CheXpert推理集（CheXpert_graphs.json）的RadGraph标注数据。
test.json包含针对50份去标识化CheXpert报告的两套独立的持证放射科医师标注集，共涵盖1473个实体与1106条关系；CheXpert_graphs.json包含由名为RadGraph基准的深度学习模型自动生成的、针对500份去标识化CheXpert报告的标注数据，共涵盖13783个实体与9908条关系，并附带对应胸部X光片的映射关联信息。
关于CheXpert_test.json（与test.json一致）与CheXpert_graphs.json文件的文档说明，以及完整RadGraph数据集，可通过以下链接获取：https://doi.org/10.13026/hm87-5p47。