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數(shù)據(jù)挖據(jù)和深度學習方法以及在生物信息學和醫(yī)療健康領域的應用

發(fā)布時間:2017-06-22 瀏覽:

講座題目:數(shù)據(jù)挖據(jù)和深度學習方法以及在生物信息學和醫(yī)療健康領域的應用

講座人:張朝陽 教授

講座時間:16:00

講座日期:2017-6-22

地點:長安校區(qū) 文津樓3段4層 計算機科學學院報告廳

主辦單位:計算機科學學院

講座內(nèi)容:The big data analytics depend on the data miningand machine learning methods. In this talk I will briefly introduce the newadvances of big data research in the United Stated of American and then presenttwo data mining and machine learning methods and their applications in bothbioinformatics and healthcare risk prediction. A new Bayesian learning andoptimization model (BLOM) was developed in our Data Mining and BioinformaticsLaboratory for inferring gene regulatory networks from time series microarraydata. This approach successfully identified hub genes and several importantgene regulation relationships in the pathways and also addressed the dynamicchange of biological networks in the course of the treatment and recovery ofdifferent species. In the second part of the talk, I will introduce multi-labelclassification and deep learning method for the health and disease riskprediction using physical exam records and traditional Chinese medicine data.

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