MultiD4CAD:由CT和冠状动脉疾病分析的临床特征组成的多模式数据集
Francesco Prinzi1, Carmelo Militello2, Giulia Sollami3,4
1Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, 90127, Palermo, Italy.
Scientific data
|September 26, 2025
概括
多D4CAD数据集将冠状动脉疾病 (CAD) 患者的成像和临床数据联系起来. 本资源有助于开发预测模型,以便更好地做出临床决策,并了解CAD.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 数据科学数据科学数据科学
背景情况:
- 临床决策支持系统 (CDSS) 需要强大的数据集来进行预测建模.
- 冠状动脉疾病 (CAD) 是一个重要的心血管问题.
- 多模式数据,包括成像和临床标记,可以提高诊断准确度.
研究的目的:
- 介绍疑似CAD患者的MultiD4CAD数据集.
- 为开发和验证CAD的预测模型提供一个验证的数据集.
- 促进放射学,深度学习和心血管疾病的CDSS方面的研究.
主要方法:
- 收集了可疑CAD患者的多式联络数据.
- 包括冠状动脉计算机断层扫描血管学 (CCTA) 成像数据与表心 (EAT) 和周冠状动脉 (PAT) 脂肪组织细分.
- 纳入的临床数据,包括CAD风险因子生物标志物和CAD疾病标签.
主要成果:
- MultiD4CAD数据集使得使用放射学和深度学习来训练预测模型成为可能.
- 已验证的EAT和PAT细分可用于高级分析.
- 数据集揭示了成像特征,临床生物标志物和CAD状态之间的相关性.
结论:
- MultiD4CAD是推进心脏病学中CDSS的宝贵资源.
- 该数据集支持CAD分类,细分,放射学和深度学习的研究.
- 使用MultiD4CAD进行进一步的调查可以提高对CAD结果的理解和预测.
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