Broad and Deep Learning of Big Heterogeneous Health Data for Medical AI

Speaker: Vincent S. Tseng (National Chiao Tung University, Taiwan)

Abstract

In healthcare domains, large-scale heterogeneous types of data like medical images, vital signs, electronic health records (EHR), genome, etc., have been collected constantly, forming the valuable big health data. Broad and deep mining/learning of these big heterogeneous biomedical data can enable innovative Medical AI applications with rich research lines/challenges underlying. In this talk, I will introduce recent developments and ongoing projects on the above topic, especially in intelligent diagnostic decision support and disease early detection by using various advanced data mining/deep learning techniques including image analysis (for medical images), multivariate time-series analysis (for vital signs like ECG/EEG), patterns mining (for EHR), text mining (for medical notes), sensory analysis (for sensory data like air pollutants) as well as data fusion methods for integrated modeling. Some innovative applications on Medical AI with breakthrough results based on the developed techniques, as well as the underlying challenging issues and open opportunities, will also be addressed.

Speaker BioVincent S. Tseng is currently a Distinguished Professor at Department of Computer Science and Director for Institute of Data Science and Engineering in National Chiao Tung University, Taiwan. He was the Chair for IEEE Computational Intelligence Society Tainan Chapter during 2013-2015 and the President of Taiwanese Association for Artificial Intelligence during 2011-2012. Dr. Tseng has a wide variety of research interests covering data mining, machine learning, biomedical informatics, mobile sensing technologies. He has published more than 350 research papers as well as 15 patents held and filed. He has been on the editorial board for a number of top journals like IEEE Trans. Knowledge and Engineering (TKDE), IEEE Journal on Biomedical and Health Informatics (JBHI), ACM Trans. Knowledge Discovery from Data (TKDD), Data Mining and Knowledge Discovery (DMKD), and serving as organizing/program committee for leading conferences like KDD, ICDM, CIKM, PAKDD, AAAI, etc. He the core committee and overseeing the directions/architecture of big data/AI platforms and interdisciplinary applications for various governmental and industrial units in Taiwan. He is a Distinguished Scientist Member of ACM and Senior Member of IEEE, as well as the recipient of 2014 K. T. Li Breakthrough Award, 2018 IT Elite Award, 2015 Outstanding Research Award and 2018 FutureTech Breakthrough Award by Ministry of .