PheMIME:一个互动的Web应用程序和知识库,用于现象广泛,多机构的多病症分析
Siwei Zhang1, Nick Strayer2, Tess Vessels3
1Department of Biostatistics, Vanderbilt University, Nashville, TN, USA.
medRxiv : the preprint server for health sciences
|August 7, 2023
概括
整个现象的多机构多病态探索器 (PheMIME) 工具有助于研究人员研究跨机构的疾病模式. 它可以发现新的疾病关联,并比较电子健康记录中的多病症数据.
科学领域:
- 计算生物学是一种计算生物学.
- 医疗信息学 医疗信息学
- 基因组学就是基因组学.
背景情况:
- 多病性,即多种疾病的同时发生,是日益严重的全球卫生挑战.
- 了解疾病相互作用对于制定有效的预防和治疗策略至关重要.
- 目前用于研究多病态模式的工具和数据集是有限的,特别是在多样化的人口中.
研究的目的:
- 开发一种新的工具,全现象的多机构多病态探索器 (PheMIME),用于探索和比较多病态模式.
- 促进在多个机构中发现强大且可互操作的疾病关联.
- 解决综合多发病性研究工具和数据集的缺口.
主要方法:
- 利用大规模的电子健康记录 (EHR) 系统.
- 综合综合统计数据从疾病多病症的全现象分析.
- 开发了交互式可视化和动态分析功能,包括一个增强的关联Subgraphs工具.
主要成果:
- PheMIME整合了来自三个主要机构的数据:范德比尔特大学医学中心,马萨斯州布里格姆总医院和英国生物银行.
- 该工具允许在系统内和跨系统的多病态模式进行交互式探索和比较.
- 通过对精神分裂症的案例研究证明了它的实用性,强调了它发现疾病集群和网络的能力.
结论:
- PheMIME为推进多病症研究提供了一个有价值的平台.
- 有助于识别新型疾病的关联和模式.
- 通过实现跨机构数据分析,促进协作研究和个性化医疗方法.
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