MEDLIFE2026

2026 12th International Conference on Health, Medicine and Life Sciences

Conference Date: May 23-25, 2026Location: Suzhou, China

Website: http://www.medlifescience.com/2026/05/en/home

Keynote Speakers

The information about the Keynote Speakers of MEDLIFE2026 is as follows, which will be updated regularly.

Dr. Alex Kuo, Professor

School of Health Information Science, University of Victoria, Victoria, Canada

Biography

Dr. Alex Kuo holds a PhD from the Department of Computer Science, University of Nottingham, UK. He is a full time professor at the School of Health Information Science, University of Victoria (UVic). He was a visiting scholar at the Department of Computer Science, Politecnico di Milano, Italy (2023), the Center for Expanded Data Annotation and Retrieval (CEDAR), School of Medicine, Stanford University, USA (2016), and the Electronic Commerce Resource Centre (ECRC), Georgia Tech (2000). Now, he is the chair of Special Interest Group on Big Data for Healthcare, Medicine and Biology at IEEE Technical Committee on Big Data. With over 20 years of programming and data analysis practical as well as research experience, he has over 170 peer-reviewed publications. His research interests include Cloud Computing & Big Data application to healthcare, health data interoperability, health database & data warehousing, data mining application in healthcare, e-health and clinical decision support system.

Topic

AI in Big Data Analytic for Healthcare

Abstract

This keynote examines the transformative influence of artificial intelligence and big data on modern healthcare systems. It brings together researchers, practitioners, and industry leaders to explore breakthroughs in AI-powered diagnostics, predictive analytics, and personalized medicine. The session also delves into big data strategies for managing large-scale healthcare datasets, strengthening clinical decision-making, and streamlining operational workflows. Core themes include an overview of cutting-edge AI methodologies, the role of AI in advancing big data analytics, and practical insights into overcoming challenges in AI adoption.

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