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西南大学计信院前沿学术报告

发布时间:2016-11-09 来源:本站原创 作者:本站编辑   浏览次数:

西南大学计信院前沿学术报告

Southwest University IT Faculty Seminar

时间:2016年11月14日(星期一)下午3:00

地点:西南大学计信院学术报告厅(第25教学楼一楼0114)

题目The Future of Healthcare Analytics

演讲人:Dr. Sheng-Chuan Wu,  Franz Inc

报告人简介:Dr. Sheng-Chuan Wu is a Vice President at the leading Artificial Intelligence and Semantic Technology company, Franz Inc, in Silicon Valley. While at Franz, Dr. Wu has collaborated with Bioinformatics experts from Harvard Medical School, Stanford University and Astra Zeneca, working with massive biological data. He has been focusing on Semantic Technology over the last 10 years, and routinely lectured and keynoted on Artificial Intelligence and Semantic Technology at conferences. Most recently, he keynoted at PRICAI2016, CCKS2016, KMO2016 and KSEM2015 on Healthcare Analytics. He has, since 2007, conducted more than 20 weeklong workshops on Semantic Technology and Artificial Intelligence in Asian countries. Dr. Wu has also consulted on several Big Data and Semantic Technology projects in theUSand Asia.

内容摘要: Since sequencing of the human genome in 2003, we have dreamed about managing patient health more effectively based on their genomic profiles. Such a dream remains elusive. “The fundamental difficulty lies in the complexity of biological systems that have evolved through billions of years.” On the other hand, major progress can be and has been made in "personalized medicine" by applying AI machine learning on massive patient medical data accumulated. In essence, we can uncover new insight from the data to improve patient health without knowing the biology behind it. Such new insight is then added back into the medical knowledge to form a richer knowledge graph for personalized medicine, predictive patient modeling, patient risk assessment, public health monitoring, etc. Exploiting patient medical data brings another set of management problems, namely the heterogeneous nature of data sources and taxonomies, the enormous size of data volume, and huge analytic processing requirements. At this talk, we will discuss all these issues and show some case studies at a major research hospital in New York City.