一个儿科心电图数据库,包括疾病诊断,覆盖11643名儿童
Jian Tan1, Haoyi Fan2, Jiawei Luo1
1ZhengZhou University, Zhengzhou, 450001, China.
Scientific data
|May 26, 2025
概括
推出了一套新的儿科心电图 (ECG) 数据集,用于诊断0-14岁儿童的19种常见心血管疾病. 本资源支持用于儿科心血管疾病检测的深度学习.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 儿科 儿科 儿科
背景情况:
- 电心电图 (ECG) 对于诊断心血管疾病至关重要.
- 现有的心电图数据集主要集中在成年人身上,缺乏特定疾病的诊断.
- 对于人工智能驱动的诊断,有很大需要全面的儿科心电图数据.
研究的目的:
- 专门为0-14岁儿童开发和展示一套新的心电图数据库.
- 为儿科人口提供详细的心血管疾病诊断.
- 促进深度学习模型的发展,用于儿童心血管疾病的识别.
主要方法:
- 从11,643名住院儿童 (2018-2024) 收集了14,190份儿科心电图记录 (12-和9-).
- 标准化的心电图数据,采样频率为500Hz,记录长度为5-120秒.
- 根据AHA/ACC/HRS指南和中国专家的共识编码的ECG记录,为19种常见的儿科心血管疾病分配标签.
主要成果:
- 该数据集包含14,190个儿科心电图记录.
- 3,516条记录被诊断为心血管疾病,涵盖了19种常见疾病.
- 包括心肌炎,心肌病,先天性心脏病和川崎病等疾病.
结论:
- 这种精心策划的儿科心电图数据库解决了现有资源的关键缺口.
- 该数据集提供了宝贵的诊断数据,用于培训和验证儿科心脏病学中的深度学习算法.
- 能够改善儿童心血管疾病的智能诊断.
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