连续的多式联络数据供应链和可扩展的临床决策支持,用于瘤学
Jee Suk Chang1, Hyunwook Kim2, Eun Sil Baek3
1Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
NPJ digital medicine
|February 27, 2025
概括
一个新的临床决策支持系统 (CDSS) 整合了各种患者数据,以改善癌症护理. 这种多式联络数据框架增强了决策和患者的结果,显示了瘤学的巨大潜力.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
背景情况:
- 瘤学中的临床决策是复杂的,通常需要整合各种患者数据.
- 现有的系统可能无法有效利用多式联运数据,包括临床,基因组和成像信息.
- 学术癌症中心在管理和分析大规模患者数据集方面面临着挑战.
研究的目的:
- 开发和评估一个临床决策支持系统 (CDSS),整合用于癌症患者护理的多式联络数据.
- 建立一个强大的数据集成框架 (Yonsei癌症数据库 - YCDL) 持续收集和更新数据.
- 评估多式联络数据集成对临床决策和患者结果分析的影响.
主要方法:
- 开发了Yonsei癌症数据库 (YCDL) 数据集成框架,用于多模式数据集 (临床,基因组,成像).
- 实施了质量控制措施 (143个逻辑比较) 以确保数据准确性 (外科:92.6%,分子病理:98.7%).
- 利用提取-转换-负载 (ETL) 过程与自然语言处理进行数据转换和生存分析,按瘤阶段分层.
主要成果:
- YCDL框架成功地整合了11种癌症类型的17万多名患者的多式联络数据.
- 存活分析显示了患者结局的显著阶段依赖差异.
- 在CDSS仪表板有效地可视化患者的轨迹和关键里程碑.
- 瘤专业人士报告说,他们对CDSS的满意度很高 (得分>4/5).
结论:
- 通过YCDL框架的多模式数据集成显著提高了瘤学的临床决策.
- 开发的CDSS展示了通过数据驱动的洞察力改善患者治疗结果的潜力.
- 未来的研究应该专注于验证这个综合数据框架的通用性和可扩展性.
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