Achieving Flexible Fairness Metrics in Federated Medical Imaging

The Dataset published with our paper "Achieving Flexible Fairness Metrics in Federated Medical Imaging" on Nature Communications.
We curate a multi-center dataset for cervical cancer segmentation that includes 678 patients from four hospitals. This diverse dataset allows for a more comprehensive analysis of model performance across different population groups, ensuring the findings are applicable to a broader range of patients.

本数据集随我们发表于《自然-通讯》（Nature Communications）的论文《实现联邦医学成像中的灵活公平性指标》（Achieving Flexible Fairness Metrics in Federated Medical Imaging）一同发布。我们构建了面向宫颈癌分割任务的多中心数据集，该数据集包含来自四家医院的678名患者。该多样化数据集支持对不同人群组的模型性能开展更为全面的分析，从而确保研究结果可推广至更广泛的患者群体。