Presented by Dr. Dejing Dou
Professor, University of Oregon, Computer and Information Science Department
UPDATE: A PDF of Dr. Dejing Dou’s presentation is available for download.
Ontologies have been well used in the biomedical and health domains. Semantic data mining refers to the data mining tasks that systematically incorporate domain knowledge, especially formal semantics, into the process. The use of ontologies in mining healthcare and medicine data is a natural fit. In this talk, we focus on the use of formal (Semantic Web) ontologies in two data mining and deep learning tasks in health datasets. We applied semantic association mining in electronic health records to discover indirect (hidden) associations among diseases and drugs. We also applied ontology-based deep learning in a health social network to predict human physical activities.
Dr. Dejing Dou is a Professor in the Computer and Information Science Department at the University of Oregon and leads the Advanced Integration and Mining (AIM) Lab. He received his bachelor degree from Tsinghua University, China in 1996 and his Ph.D. degree from Yale University in 2004. His research areas include artificial intelligence, data mining, data integration, information extraction, and health informatics. Dejing Dou has published more than 60 research papers, some of which appear in prestigious conferences and journals like AAAI, KDD, ICDM, SDM, CIKM, ISWC, JIIS, and JoDS. His DEXA’15 paper received the best paper award. His KDD’07 paper was nominated for the best research paper award. He is on the Editorial Boards of Journal on Data Semantics and Journal of Intelligent Information Systems. He has been serving as program committee members for various international conferences and as program co-chairs for four of them. Dejing Dou has received over $4.5 million PI research grants from the NSF and the NIH.
May 18, 2017 (Chapter Meetings, 3rd Thursday)
8:30 – 9:00 am – Sign In
9:00 – 10:15 am – Presentation
10:15 – 10:30 am – Break, Chapter Announcements
10:30 – 11:30 am – Presentation continued
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