16万例胸部X光数据集公开，助力医疗AI报告生成研究
ReXGradient-160K: A Large-Scale Publicly Available Dataset of Chest Radiographs with Free-text Reports
- 整合3大美国医疗系统10.9万患者数据，每份报告配多张影像
- 含14万训练、1万验证、1万公开测试数据，另有1万私有测试集
- 适合医疗影像AI、自动报告生成模型开发者使用
我们提出ReXGradient-160K，目前规模最大的公开胸部X光数据集，涵盖160,000例胸部X光检查，来自109,487名独特患者，覆盖3个美国医疗系统共79个医疗机构。该数据集包含每项检查的多张影像及详细放射科报告，对开发与评估医学影像AI系统和自动化报告生成模型具有重要价值。数据按140,000例训练、10,000例验证、10,000例公开测试划分，并保留10,000例私有测试集用于ReXrank基准评估。本数据集将开源至https://huggingface.co/datasets/rajpurkarlab/ReXGradient-160K，旨在加速医学影像AI研究并推动自动化放射分析技术发展。
原文摘要 · Abstract (English)
We present ReXGradient-160K, representing the largest publicly available chest X-ray dataset to date in terms of the number of patients. This dataset contains 160,000 chest X-ray studies with paired radiological reports from 109,487 unique patients across 3 U.S. health systems (79 medical sites). This comprehensive dataset includes multiple images per study and detailed radiology reports, making it particularly valuable for the development and evaluation of AI systems for medical imaging and automated report generation models. The dataset is divided into training (140,000 studies), validation (10,000 studies), and public test (10,000 studies) sets, with an additional private test set (10,000 studies) reserved for model evaluation on the ReXrank benchmark. By providing this extensive dataset, we aim to accelerate research in medical imaging AI and advance the state-of-the-art in automated radiological analysis. Our dataset will be open-sourced at https://huggingface.co/datasets/rajpurkarlab/ReXGradient-160K.
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