MIMIC-IV-ECG-Ext-ICD: Diagnostic labels for MIMIC-IV-ECG

The number of publicly available ECG datasets has increased tremendously in the past few years and several of these datasets have developed into widely used benchmarking datasets. However, most of them exhibit a common limitation, namely the reliance on retrospective annotation and a lack of clinical ground truth. This represents a serious limitation compared to closed in-hospital datasets. To circumvent this issue, we propose the MIMIC-IV-ECG-Ext-ICD dataset by linking the samples from the MIMIC-IV-ECG dataset to clinical ground truth from the MIMIC-IV dataset, in the form of ED and hospital discharge diagnoses. We release this derived dataset to foster further research on ECG-based prediction models with clinical ground truth and build a resource for benchmarking clinical ECG prediction models.公开可用的心电图（Electrocardiogram, ECG）数据集数量在过去数年中大幅增长，其中已有多个发展为广泛使用的基准测试数据集。然而，绝大多数此类数据集存在一个共性局限：依赖回顾性标注，且缺乏临床真实标注（clinical ground truth）。相较于封闭院内数据集，此类缺陷会构成严重的应用局限性。为规避这一问题，我们通过将MIMIC-IV-ECG数据集的样本与MIMIC-IV数据集提供的急诊室（Emergency Department, ED）及住院出院诊断形式的临床真实标注进行关联，构建了MIMIC-IV-ECG-Ext-ICD数据集。我们公开发布这一衍生数据集，旨在推动基于心电图的带临床真实标注的预测模型相关研究，并为临床心电图预测模型的基准测试提供支撑资源。