报 告 人：J. Jian-Jian Ren 教授（University of Maryland-College Par）
报告题目：BIGDATA Analysis with Application to Vaccine-Adverse Event Data
报告时间：2017年7月6日15:30
报告地点：静远楼1506学术报告厅
报告人简介：
J. Jian-Jian Ren, Professor, Statistics Program, Department of Mathematics, University of Maryland-College Par .
报告摘要：
Big data problems in biomedical research involve data wrangling challenge; that is to identify and extract data attributes or characteristics within unstructured data and find common attributes across a broad range of data types. It is well-known that before a particular vaccine was marketed, clinical trials had already identified some adverse symptoms associated with such vaccine. But so far there has not been any statistical analysis conducted in attempting to identify the cross-board patterns of all reported adverse symptoms related to the vaccines. Here we consider an analysis of the FDA Vaccine Adverse Event Reporting System (VAERS) data to characterize the cross-board patterns of all reported adverse symptoms or events related to the vaccines. Some recently developed data visualization techniques for the big data analysis are employed to handle the large dimension FDA VAERS dataset which consists of large dimension of nominal (categorical) variables and does not have obvious or clear structure. This work is joint with Professor T. Sun of UND-College Park, Professor Oliver He of University of Michigan Medical School - Ann Arbor, and Professor Y. Zhang of UMB School of Medicine – Baltimore. Baltimore.