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Academic Report: Looking for Disease Diagnostic Models from Large-scale Biomedical Data





Topic: Looking for disease diagnostic models from large-scale biomedical data

Time: 900-1100, June 13th (Tuesday), 2017

Venue: 404, Building of Science, West Campus

Lecturer: Hao Wu

About the lecturer: Wu received his Bachelor Degree from the Department of Electrical Engineering, Tsinghua University; Doctoral Degree from the Department of Biostatistics, Johns Hopkins University. Starting his career in the Department of Biostatistics and Bioinformatics, Emory University in 2010, he is now a tenured Associate Professor. His research fields are statistical methods of high-throughput genome sequence database (including Gene chip, RNA-seq, ChIP-seq, BS-seq) and the development of computing tools. Dr. Wu is the first author of many academic papers on international top journals, including: Nature Method, Genome Research, Genome Biology, Nucleic Acids Research, Bioinformatics, and Biostatistics. He has published a total of 56 papers cited 5500 times.

About the lecture: The rapid developments of bio-technologies and computational methods have evolutionarized the biomedical research. The enormous amount of data generated from various high-throughput technologies provide unprecedented opportunities for advancing medical practice, however, to make better sense of the data requires the development of novel statistical/computational methods. In this talk, Dr. Wu will briefly introduce two on-going projects in his research group on constructing disease diagnostic models from large-scale biomedical data. The first one is using cell-free DNA methylation profile for disease prediction; the second one is the development of a CADx (Computer-aided diagnosis) system for Vogt-Koyanagi-Harada (VKH) disease based on retina image.

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