报告人：闽江学者讲座教授Shengrui Wang (王声瑞)
报告题目：Feature-weighted Survival Learning Machine for COPD Failure Prediction
时间：2017-12-15 (星期五) 9:00 ~ 11:00
地点：新区数信大楼507报告厅
主办：数学与信息学院、数字福建环境监测物联网实验室
参加对象：数信学院感兴趣教师及研究生
报告摘要：Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting such failure is crucial to early intervention and decision-making, making this a very important research issue. Current analysis methods address all risk factors in medical records indiscriminately and therefore generally suffer from ineffectiveness in real applications, mainly because many of these factors relate weakly to prediction. Numerous studies have been done on selecting factors for survival analysis, but their inherent shortcomings render these methods inapplicable for failure prediction in the context of unknown and intricate correlation patterns among risk factors. These difficulties have prompted us to design a new Cox-based learning machine that embeds the feature weighting technique into failure prediction. In order to improve predictive accuracy, we propose two weighting criteria to maximize the area under the ROC curve (AUC) and the concordance index (C-index), respectively. At the same time, we perform a Dirichlet-based regularization on weights, making differences between factor relevance clearly visible while maintaining the model’s high predictive ability. The experimental results on real-life COPD data collected from patients hospitalized at the Centre Hospitalier Universitaire de Sherbrooke (CHUS) demonstrate the effectiveness of our learning machine and its promise in clinical applications.
报告人简介：王声瑞（Shengrui Wang）, 加拿大籍华人，加拿大舍布鲁克大学计算机系(University of Sherbrooke)终身教授，博士生导师。1989年毕业于法国格勒诺布尔国立理工学院(Institut National Polytechnique de Grenoble)并获得计算机博士学位。王声瑞教授的研究涉及数据挖掘、模式识别、人工智能、图像处理和理解、知识采集、信息系统、神经网络、优化等众多科学领域，在高维数据、类数据及序列数据聚类方面具有国际公认的出色成果，并成功地应用于生物信息学、临床数据、 财经、英特网、汽车导航、图像数据库、智能环境、雷达监测等领域。王声瑞教授1993年起连续27年获得加拿大国家自然科学和工程技术研究基金(NSERC)创新研究资助，主持多项重大研究资助项目，并在2010获得NSERC的加速创新研究特资资助。自2010起任加拿大国家自然科学和工程技术研究基金会计算机委员会核心成员，先后担任计算机方法分会主席（2013-2014），计算机-数学-统计学研究工具及仪器基金评选委员会主席（2015-2016）。
