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Big EHR Data: A Directed-Graph Network of Disease-Disease Interactions

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讲座题目:Big EHR Data: A Directed-Graph Network of Disease-Disease Interactions
讲座人: 武虎林教授
讲座时间:15:00
讲座日期:2017-6-28
地点:数学与信息科学学院学术报告厅

Abstract: Based on two health care Big Data sets with sample sizes n=10 million and 50 million respectively, we derived different types of disease-disease networks using the longitudinal information. We establish both short-term and long-term directed networks as well as the simultaneously-occurring undirected network of 1660 PheWAS disease groups. Among 2,753,940 possible disease pairs, we identified 646,969 for long-term and 10,587 for short-term significant pairs,respectively, which were observed in at least five patients and had relative risk (RR) > 1 with significance at 0.05 level after Bonferroni corrections. Among 1,376,970 possible disease pairs of simultaneous occurrence, we identified 18,137 which were observed in at least five patients and had RR > 1 with significance at 0.05 level after Bonferroni corrections. Based on the results, we define a new disease Influence Factor (IF). For the short-term network, the top diseases with the highest IF is more likely pregnancy related; while for the long-term network, it is more kidney related diseases. More clinical implications from these findings will be discussed. I will also discuss the challenges in Big Data research and future trends.

报告人简介:

  武虎林教授1994年毕业于弗罗里达州立大学。目前任休斯敦的德克萨斯大学健康科学中心公共卫生学院生物统计系主任。教授的研究兴趣包括生物医学和健康科学大数据分析,复杂的高维数据分析、微分方程模型的统计方法和理论,计算系统生物学以及生物信息学在免疫学和传染病上的应用。教授已在生物统计、生物信息、计算生物学、免疫学及传染病预测等研究领域发表了100多篇研究论文和两本专著。


 
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