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讲座:Optimal Genetic Testing of Families

发布者:人力资源办公室    发布时间:2021-11-10

题 目:Optimal Genetic Testing of Families

嘉 宾:Xikuan Wang, PhD candidate, University of Chicago

主持人:花成  助理教授  上海交通大学安泰经济与管理学院

时 间:2021年11月12日(周五) 09:00-10:30

地 点:A407&腾讯会议

 (校内师生如需会议号和密码,请发送电邮至xuziqing@sjtu.edu.cn获取) 

内容简介

Through the laws of inheritance, knowing an individual’s genetic status informs disease risk for family members, but current protocols for deciding who to genetically test only consider one person at a time rather than design an optimal testing plan for the entire family. We develop a Markov decision process framework for maximizing the net-benefits of genetic testing, which integrates a Bayesian network of genetic statuses, with a functional representation of cost-effectiveness. Our model provides a contingent sequence of family members to test one-at-a-time, i.e., a plan that dynamically incorporates new test results, revealed sequentially at random, to decide who next to test. Using the BRCA1/2 genes as a test case, we show that our policy can simultaneously increase quality-adjusted life years while decreasing testing costs, resulting in substantial benefits to social welfare. Thus, our framework offers a promising and powerful new approach to genetic testing of populations.

演讲人简介

Kanix Wang is a Principal Researcher with the Healthcare Analytics Laboratory and an Adjunct Assistant Professor of Statistics at Chicago Booth. He studies business analytics, healthcare operations, and natural language processing, a subfield of artificial intelligence. His work has focused on the deep integration of healthcare innovations and operations. In particular, his research interests are shaped by the emerging trend towards the adoption of machine learning and genetic-related technology in healthcare.

His work has been published in journals including INFORMS Journal on Computing and Nature Genetics. One of his papers was selected as a Finalist for the William Pierskalla Award for Best Paper in Healthcare. His research has been featured in New Scientist, Newsweek, Quartz, Science Daily, and Time.

Before getting his Ph.D. at the University of Chicago, he earned a bachelor's degree in mathematics and biology at Wabash College.

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