Consore:一个强大的联合数据挖掘工具,推动法国研究网络加速癌症研究
Julien Guérin1, Amine Nahid2, Louis Tassy3
1Institut Curie, 75005 Paris, France.
International journal of environmental research and public health
|February 24, 2024
概括
康索尔网络利用了来自法国11个中心的100多万癌症患者的真实数据. 这种先进的系统通过结构化医疗记录和创建大型患者队列,使得癌症研究更快,更有效.
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:
- 关于癌症患者健康和护理的真实世界数据 (RWD) 反映了临床实践,提供了必要的真实世界的证据.
- 先进的信息技术对于在研究中收集,合格和重用RWD至关重要.
研究的目的:
- 介绍Consore,这是一个由UNICANCER开发的联合研究网络,用于分析癌症患者数据.
- 突出Consore在结构化和利用大规模电子医疗记录数据方面的能力.
主要方法:
- UNICANCER成立了Consore,这是一个联合网络,连接了法国11个综合性癌症中心.
- 自然语言处理用于从电子医疗记录中构建治疗管理数据.
- 一个共同的数据模型和联合搜索工具可以根据患者,瘤和治疗特征创建队列.
主要成果:
- 目前,Consore在法国11个癌症中心开展业务,处理约130万癌症患者 (6500万病历) 的数据.
- 该系统成功地结构和协调了数据,促进了大型患者队列的创建,这对罕见癌症研究有利.
- 协会的联合架构和共享数据模型支持监管合规,加速研究.
结论:
- 康索尔作为一个重要的数据挖掘工具,推动法国癌症中心进入大数据时代.
- 该网络的技术架构和数据模型简化了监管合规性,加速了癌症研究项目.
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