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Keynote Speaker I

Prof. Hyoungseop Kim
Kyushu Institute of Technology, Japan

Prof. Hyoungseop Kim received his B.A. degree in electrical engineering from Kyushu Institute of Technology in 1994, the Masters and Ph.D. degree from Kyushu Institute of Technology in 1996 and 2001, respectively. He is a professor in the department of control engineering at Kyushu Institute of Technology. His research interests are focused on medical application of image analysis.


Speech Title :"Computer Aided Diagnosis Based on Pattern Recognition Technique"


Abstract: For reducing the load to radiologist and improving of detection accuracy, a CAD (Computer Aided Diagnosis) system is expected from medical fields. In the medical image processing fields, some related works are reported to develop the CAD system as helpful technical issues. In this talk, I will introduce why CAD is required in medical field. Then I would like to some CAD systems for supporting to radiologists based on pattern recognition techniques.


Keynote Speaker II

Prof. Tae-Seong Kim

Professor, Dept. of Biomedical Engineering, Kyung Hee University, Republic of Korea
Director, Bioimaging and Brain Engineering Laboratory, Kyung Hee University, Republic of Korea


Tae-Seong Kim received the B.S. degree in Biomedical Engineering from the University of Southern California (USC) in 1991, M.S. degrees in Biomedical and Electrical Engineering from USC in 1993 and 1998 respectively, and Ph.D. in Biomedical Engineering from USC in 1999. After his postdoctoral work in Cognitive Sciences at the University of California at Irvine in 2000, he joined the Alfred E. Mann Institute for Biomedical Engineering and Dept. of Biomedical Engineering at USC as Research Scientist and Research Assistant Professor. In 2004, he moved to Kyung Hee University in Korea where he is currently Professor in the Department of Biomedical Engineering. His research interests have spanned various areas of biomedical imaging, bioelectromagnetism, neural engineering, and assistive biomedical lifecare technologies. Dr. Kim has been developing advanced signal and image processing methods, pattern classification, machine learning methods, novel medical imaging modalities, and rehabilitation technologies. Dr. Kim has published more than 300 papers and seven international book chapters. He holds ten international and domestic patents and has received nine best paper awards.


Speech Title: "Deep Learning Methodologies in Smart Assistive Lifecare Technologies"


Abstract: Due to the rapid increase in the elderly population, the field of assistive lifecare technologies is also advancing rapidly. The goal of assistive lifecare technology is to increase the quality of life and promote the health of residents proactively for ambient assisted living. In general, smart sensors and devices are active components in smart assistive lifecare technologies. Also they provide alternative means of e-healthcare over caregivers or institutional care. In this presentation, how deep learning methodologies can be applied to smart multi-modal sensors and devices for smart assistive living. Various topics including human activity recognition, human motion recognition, life event detection, lifelogging, etc. are covered.


Plenary Seaker I

Prof. Taesung Park

Seoul National University, South Korea


Prof. Taesung Park received his B.S. and M.S. degrees in Statistics from Seoul National University (SNU), Korea in 1984 and 1986, respectively and received his Ph.D. degree in Biostatistics from the University of Michigan in 1990. From Aug. 1991 to Aug. 1992, he worked as a visiting scientist at the NIH, USA. From Sep. 2002 to Aug. 2003, he was a visiting professor at the University of Pittsburgh. From Sep. 2009 to Aug. 2010, he was a visiting professor in Department of Biostatistics at the University of Washington. From Sep. 1999 to Sep. 2001, he worked as an associate professor in Department of Statistics at SNU. Since Oct. 2001 he worked as a professor and currently the Director of the Bioinformatics and Biostatistics Lab. at SNU. He served as the chair of the bioinformatics Program from Apr. 2005 to Mar. 2008, and the chair of Department of Statistics of SNU from Sep. 2007 and Aug. 2009. He has served editorial board members and associate editors for the international journals including Genetic Epidemiology, Computational Statistics and Data Analysis, Biometrical Journal, and International journal of Data Mining and Bioinformatics. His research areas include microarray data analysis, GWAS, gene-gene interaction analysis, and statistical genetics.


Speech Title: "Hierarchical Structural Components Models for High Dimensional Omics Data"


Abstract: Identification of good biomarkers is one of the most challenging issues in personalized medicine era. Although many methods have been developed to identify candidate biomarkers using only the omics data available, it is well known that the use of biological hierarchical information would increase of the power of identifying biomarkers. We proposed hierarchical structural components models (HisCoM) for taking into account the hierarchical structure of biological data. In our earlier work, HisCoM was shown to perform well by considering the hierarchical structure of genetic variants, genes and pathway. We extended HisCoM for the analysis of miRNA and mRNA data. We show that HisCoM can successfully take into account the hierarchical inhibition relationship between one miRNA and multiple mRNAs. In real data analysis, our HisCoM successfully identified more informative miRNA-mRNA integration sets for survival time of pancreatic cancer patients, compared to the other existing methods. Through this application to pancreatic cancer data, our proposed model was shown to effectively identify integrated miRNA/target mRNA sets as markers for prognosis, providing a much broader biological interpretation.








Important Date

Submission Deadline Before July 05, 2018
Notification Date     On July 20, 2018
Registration Deadline Before July 30, 2018
Conference Date  August 22-24, 2018