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It’s very exciting to have this many notable speakers and experts available in relatively small settings so you can ask them questions and engage them. It really is terrific. I’ve been impressed by the number of different kinds of topic and areas of exploration, and the level of expertise represented here.                 








Prof Lesley Curtis  
Interim Executive Director, Duke Clinical Research Institute, Duke University Medical Centre


Programme >

Artificial Intelligence Symposium
Artificial Intelligence (AI) in Medicine - Current and Future Direction

 Track type: Symposium

Date: 17 Sep 2021


 Time: 1050 - 1220

Location: Seminar Room 2

At present, we are facing an existential global health crisis – the outbreak of novel coronavirus virus (COVID-19). This symposium aims to describe the role of data science and AI that can be applied for digital transformation in tackling major clinical problems and diseases. These digital technologies include the internet of things (IoT) with next generation tele-communication network (5G), big data analytics and AI using deep learning. They are highly inter-related: the proliferation of IoT such as devices, instruments in hospitals and clinics enable the establishment of a highly interconnected digital ecosystem, enabling real time data collection at scale, which could then be utilised by AI and deep learning systems to understand healthcare trends, model risks associations and predict outcomes. This symposium aims to share the principles, concepts and examples of the data science, AI, machine learning, deep learning in tackling various clinical unmet need during the COVID-19 pandemic crisis.


The Principles, Concepts and Examples of Data Science in Medicine


The Concepts of AI, Machine Learning and Deep Learning 


Speaker: Adj Asst Prof Liu Yong



The Importance of Data Curation and Governance for AI and Data Science


Speaker: Cl Assoc Prof Yeo Khung Keong



The Pearls and Pitfalls of AI in Medicine


AI vs COVID: Cutting Edge Radiology Innovation and Preparing for Future Pandemics


Panel Discussion

*Information is correct at time of update