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New Challenges in Machine Learning: Multiclass-Classification for Risk Predictions in Health Care Applications
发布时间:2019-07-25     浏览量:   分享到:

报告题目:New Challenges in Machine Learning: Multiclass-Classification for Risk Predictions in Health Care Applications

报告人:Hamido Fujita 教授

报告时间:2019815 10:00

报告地点:长安校区 文津楼三段3412

主办团队:beat365正版唯一官网生物大数据计算研究团队

报告摘要:

Discovering patterns from big data attracts a lot of attention due to its importance in discovering accurate patterns and features that are used in predictions of decision making.

The challenges in big data analytics are the high dimensionality and complexity in data representation analytics especially for on-line feature selection. Granular computing and feature selection on data streams are among the challenge to deal with big data analytics that is used for Decision making. We will discuss these challenges in this talk and provide new projection on ensemble deep learning techniques for on-line health care risk prediction. Different type of data (time series, linguistic values, interval data, etc.) imposes some difficulties to data analytics due to preprocessing and normalization processes which are expensive and difficult when data sets are raw, or imbalanced. We will highlight these issues through project applied to health-care for elderly, by merging heterogeneous metrics from multi-sensing environment providing health care predictions assisting active aging at home. We have utilized ensemble learning as multi-classification techniques on multi-data streams using incremental learning to update data change “concept drift”.  

报告人简介:

Hamido Fujita is Chair professor at Iwate Prefectural University (IPU), Iwate, Japan, and director of Intelligent Software Systems. He is the Editor-in-Chief of Knowledge-Based Systems, Elsevier since 2008, by his leadership the journal is not in Q1 and top 15 among high ranking journals. He was establishment committee member of IPU and head of Information Systems for five years (1998~2003). He received Doctor Honoris Causa from O’buda University, Budapest Hungry in 2013 on high achievement in Legacy system and Knowledge-Based technology, and he is has a title of Honorary Professor from O’buda University, Budapest, Hungary in 2011. He received honorary scholar from University of Technology Sydney, Australia on 2012. He also received honorary professorship from Xidian University, Xi’an China, and Shanghai University of Finance and Economics, China, Tongji University (Shanghai) top talent pulpit award, on 2016. He is Adjunct professor to Stockholm University, Sweden, University of Technology Sydney, National Taiwan Ocean University, Southwest Jiaotong University (Chengdu China) and others. He has supervised PhD students jointly with University of Laval, Quebec; University of Technology, Sydney, Australia; Oregon State University (Corvallis), University of Paris 1 Pantheon-Sorbonne, Paris University of Genoa, Ngee Ann Polytechnic, (Singapore), University Technology of Malaysia (Johor) and others. He has four international Patents in Software System and Several research projects with Japanese industry and partners. He is vice president of International Society of Applied Intelligence (ISAI), and Distinguished Program Committee member of IEEE SMC society, and Technical Committee member of Cyber-medical Systems, (IEEE SMC society). He has published more than 200 papers in high ranking journal and reputed international conferences, given many keynotes in many prestigious IEEE international conferences on intelligent system and subjective intelligence. He is also editor in journal of Ambient Intelligence and Humanized Computing (Springer), King Saud Journal and others. He is the founder of SoMeT Incorporation (New Software Methodologies Tools and Techniques) in year 2000, He headed a number of projects including Intelligent HCI, a project related to Mental Cloning as an intelligent user interface between human user and computers and SCOPE project on Virtual Doctor Systems for medical applications funded by Japanese Ministry of Interior Affairs and Communications.