Segment Title



18.30 – 8.55Registration startsNA 
29:00 AMEmcee WelcomeNA 
39 – 9.05Welcome Address by Prof NgiamDr Ngiam Kee Yuan
Group Chief Technology Officer, National University Health System  
Associate Professor, Yong Loo Lin School of Medicine, NUS
49.05 – 9.10Welcome Address by Prof Feng
Dr Feng Mengling                                                                                                               Senior Assistant Director, National University Health System
Assistant Professor,
Saw Swee Hock School of Public Health, NUS
59.10 – 9.30NVIDIA: The Healthcare MetaverseDr Mona Flores, Global Head of Medical AI, NVIDIA CorporationWith the current interest in the Metaverse reaching a feverish pitch, Dr Mona from NVIDIA will go over what this means for healthcare, separating what is possible for near-term adoption vs the future and its possible use cases. She will also cover the tools needed to build the experience. Join us for this session as we speak about the Healthcare Metaverse.
69.30 – 9.50Intel: Advancing Health & Life Sciences Innovation with Data-Driven AnalysisMs Wendy Bohner,
Health & Life Sciences Solution Architect, Intel Corporation
This session will cover key Health & Life Sciences trends in 2022 that are driving the need for data-driven insights.  Learn how Artificial Intelligence and Machine Learning are being applied to Accelerate Scientific Discovery, Power the Smart Hospital and Modernize Digital Infrastructure. Among the use cases to be explored: how researchers are training models to recognize rare disease, how biopharma is transforming drug discovery, diagnosis and treatment, and how patient privacy is preserved while also providing greater access to data
79.50 – 10.10MSDDr Asad Abu Bakar Ali
Director & Singapore Site Lead, Biomarker & Target Sciences (Imaging) Translational Medicine Research Centre, Singapore  MSD
810.10 – 10.30[Keynote Speaker] MIT: AI in Healthcare will Fail without Data SharingGuest of Honour: Dr Leo Anthony Celi 
Clinical Research Director, Laboratory of Computational Physiology, Massachusetts Institute of Technology (MIT)

Although the risk of re-identification from a publicly available is not zero, it is far outweighed by the harm when health data is not shared. No one group is smart enough to understand the biases that exist in health data (AI research = Arrogant & Ignorant). The only way to build artificial intelligence in healthcare is to allow multiple expertise, perspectives and lived experiences to curate and analyze digital health data in an open and fully transparent manner. This is the only way we can gain our patients’ trust, and the only way that AI will deliver equitable benefits.


910.30 – 11Morning TeabreakNA 
1011:00 AMEmcee Welcome  
1111 – 11.20HarvardDr Finale Doshi-Velez 
1211.20 – 12PanelDr Finale Doshi-Velez
Dr Judy Gichoya
Dr Anirban Bhattacharyya
Dr Barret Rush
Moderator: Dr Omar Badawi
Responsible and ethical use of AI
1312 – 12.20ASUS: Machine Learning for Healthcare: Solutions and ChallengesDr Stefan Winkler, Research Director and Acting GM, ASUS AICS Singapore

AI and machine learning have shown tremendous promise across a broad range of applications in medicine. The healthcare environment is becoming increasingly ready to embrace these solutions, which have the potential to lower healthcare costs, identify more effective treatments, and facilitate prevention and early detection of diseases. However, the development of machine learning solutions for healthcare requires paying close attention to the IT ecosystem as well as the clinical workflow.

In this talk, we will share recent advances in machine learning, computer vision, and natural language processing that are driving innovation in medicine.  We will demonstrate example solutions developed by AICS for patient care as well as hospital operations.  Finally, we will discuss challenges and future directions for the successful implementation of machine learning solutions in healthcare.

1412.20 – 1.20Lunch BreakNA 
151.20 PMEmcee Welcome  
161.20 – 1.40Huawei: Today’s Digital Healthcare Focus AreaMr Andy Tan
APAC Healthcare Ecosystem Director, Huawei Cloud
AI in healthcare is the future, but which is the priority? Is either lifesaving focus or business first. Through this presentation we will share the healthcare market interest area and explore the AI priority in the ecosystems.
171.40 – 2ST Engineering: The Landscape of AI Use Cases in HealthcareDr Clifton Phua
Chief Technology Officer, Digital Systems
ST Engineering
Healthcare excellence is important to every country, where they strive for equitable healthcare policies, better treatment outcomes for patients, and improved healthcare services and reduced cost.
182 -2.20NSCCDr Kenneth Ban
Assistant Professor, Department of Biochemistry, National University of Singapore
192.20 – 2.40Microsoft – AI in HealthcareDr Keren Priyadarshini
Regional Business Lead, Worldwide Health, Microsoft Asia
Over a decade, I identified many AI use cases in healthcare, and recently categorised them as population health, clinical, operations, and crisis management use cases. I will walk through these categories and sub-categories, and provide details on selected use cases.
202.40 – 3.10Afternoon Tea BreakNA 
213.10Emcee Welcome In addition, I will share about the types of healthcare AI practitioners and lessons learnt from working with them, as well as a self-compiled list of open source healthcare datasets.
223.10 – 3.30MSD: Driving Transformation in Healthcare through Emerging TechnologiesMs Priyanka Deva
Director, Technology Collaboration and Innovation
233.30 – 3.50   
243.50 – 4.10Tencent: Bridging Gaps in Healthcare Industry with Tencent Cloud TechnologyMs Li Chan
Healthcare Architect, Tencent Cloud
Tencent Cloud has been exploring ways to improve the quality and efficiency of healthcare industry through digital technology and Tencent AI concentrates on the entire process of medical services. Today we want to share about what we have done from disease diagnosis to treatment, including guided consultation, AI pre-diagnosis, AI-assisted diagnosis, and guided medication.
254.10 – 4.30BGIMr Liu Wei Bin
Vice President and Special Assistant to the Chairman of BGI Group
254.30 – 5.20PanelDr Leo Celi
Dr David Pilcher
Torleif Lunde, Trixie Tiangco
Moderator: Prof Ngiam Kee Yuan
The Risk of Not Sharing Data
265.20 – 5.30Closing remarks by Prof Ngiam and Prof FengNA