Expo Schedule

8.30AM - 6.00PM
400+ Registered
Recording link:https://youtu.be/fL-lX82Evb0

8.30 - 8.55
Registration Begins
Emcee Welcome
9.00 - 9.10
Welcome Address

SHADE22 co-chairs: A/Prof Ngiam Kee Yuan and Asst/Prof Feng Mengling

9.10 - 9.30
NVIDIA: The Healthcare Metaverse

Speaker: Dr Mona Flores

Global Head of Medical AI, NVIDIA Corporation

With 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.

9.30 - 9.50
Intel: Advancing Health & Life Sciences Innovation with Data-Driven Analysis

Speaker: Ms 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.

9.50 - 10.10
MSD: Data Science for Accelerating Drug Discovery: using the confluence of biology, technology, and data science for differentiating signal from noise.

Speaker: Dr Asad Abu Bakar Ali

Director & Singapore Site Lead, Biomarker & Target Sciences (Imaging) Translational Medicine Research Centre, Singapore MSD

The emergence of AI/ML has posed an important question – how do we leverage these novel tools to accelerate our research and drug discovery pipeline? Organizations must focus on a few key elements to enable a transformative impact – identifying the right question and having the right people to work on those questions using the right technology. This session will focus on why a synergy between biology, technology, and data science is critical for differentiating biological signals from noisy data and generating actionable insights for driving pipeline forward.

10.10 - 10.30
MIT: AI in Healthcare will Fail without Data Sharing

Guest of Honour and Keynote Speaker: A/Prof 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.
10.30 - 11.00
Morning Teabreak
Emcee Welcome
11.00 - 11.20
Harvard: Explainable, Statistically-Sound Batch RL for Healthcare

Speaker: Dr. Finale Doshi-Velez

Gordon McKay Professor of Computer Science, Harvard University

Responsible decision-making is tough in batch settings because policy improvement involves doing something different from the current behavior policy — but we only have data from that current behavior policy.  In this talk, I’ll describe recent work which focuses on (a) identifying where clinicians disagree and (b) only making recommendations at those decision points.  The core idea is that, statistically, we only have evidence to suggest an alternate policy in areas where we have observed clinician disagreement.  The result is a set of recommendations that has both more statistical support and is easier for clinicians to inspect for validity.  I’ll conclude with current work on explainable RL that aims to make the minimal number of changes from current clinical practice for maximal benefit.  

11.20 - 12.00
Panel Discussion: How to build trust for AI technologies in healthcare settings

Dr. Finale Doshi-Velez, Harvard University; Dr. Leo Anthony Celi, MIT; Dr. Anirban Bhattacharyya, Mayo Clinical; Dr. Barret Rush, University of Manitoba

Moderator: Dr Omar Badawi

12.00 - 12.20
ASUS: Machine Learning for Healthcare: Solutions and Challenges

Speaker: Dr 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.
12.20 - 1.20
Lunch Break
Emcee Welcome
1.20 - 1.40
Huawei: Today's Digital Healthcare Focus Area

Speaker: Mr Zhao Xi

Partner Development Director, Huawei Cloud APAC

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. 

1.40 - 2.00
ST Engineering: The Landscape of AI Use Cases in Healthcare
Speaker: Dr 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. 
2.00 - 2.20
NSCC: High Performance Computing for Accelerating Healthcare and Biomedical Research

Dr Kenneth Ban

Programme Director, (Health / Biomedical and Life Sciences), National Supercomputing Centre (NSCC)

Healthcare is becoming more data-driven with the advent of ‘omics technologies and the ability to profile multi-dimensional parameters. Analysis of these large and complex datasets can accelerate the generation and testing of hypotheses to derive new insights that can improve healthcare outcomes. As size and complexity of data continues to increase, the need for computational and storage resources has become the bottleneck in analytical pipelines.

In Singapore, the National Supercomputing Centre (NSCC) was established to support the high performance scientific computing needs for different stakeholders in academia, research communities and industry. I will discuss how NSCC works in partnership with stakeholders in the biomedical and healthcare sectors to support the computational storage and networking needs, critical for accelerating the data-intensive analytical pipelines for digital healthcare.


2.20 - 2.40
Microsoft - AI in Healthcare
Dr 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. 
2.40 - 3.10
Afternoon Teabreak
Emcee Welcome
3.10 - 3.30
MSD: Transformation and Innovation with Emerging Technologies

Speaker: Priyanka Deva

Director, Technology Collaboration and Innovation, Singapore IT Hub, MSD

Transformation and innovation have been growing in importance and urgency as the biopharmaceutical industry, enterprise, and ecosystem partners seek to accelerate the transformation to meet evolving business needs. The session aims to discuss the emerging technologies which will have an impact on the biopharmaceutical industry and how MSD is leveraging technology and innovation to enable business outcomes.

3.30 - 3.50
Amazon Web Services: AI/ML for Healthcare: AWS accelerates innovation from benchtop to bedside


 Dr Eleni Dimokidis, CTO Healthcare Asia Pacific & Japan, AWS

Juan Mejia, AWS Solutions Architect, focused on AI/ML for Healthcare

Artificial intelligence (AI) holds the potential to power precision health with a new focus on disease prevention and to support citizens to keep well across the course of their lives. With AWS’ purpose-built artificial intelligence (AI) services for vision, transcription, natural language processing, and document understanding as well as the most comprehensive ML platform, organizations can use ML to make this a reality.

3.50 - 4.10
Tencent: Bridging Gaps in Healthcare Industry with Tencent Cloud Technology

Speaker: Ms 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.

4.10 - 4.30
BGI: Large field-of-view, high-resolution spatially-resolved transcriptomics using DNA nanoball patterned arrays

Speaker: Mr Liu Wei Bin

Vice President and Special Assistant to the Chairman of BGI Group

STOmics Stereo-seq(SpaTial Enhanced Resolution Omics-sequencing) focuses on going from data to knowledge in one step-with spatially resolved, sub-cellular gene expression profiling in intact tissue slices using unbiased spatial transcriptome profiling measurements.
Built on DNA Nanoball technology, Stereo-seq is designed for in situ mRNA capture and localization. Spatially resolved molecular information can be obtained with Stereo-seq, which provides a powerful research base for advanced analysis of gene expression, cell type identification, and, cell-to-cell communication in the nascent tissue microenvironment.

4.30 - 5.10
Panel Discussion: How AI may help with the burnout issue in healthcare systems

Joe Bayer,Beth Israel Deaconess Medical Center; Tiffany Wang, UCLA Medical Center; Dr Dominic Marshall, Imperial College; Dr Sing Chee Tan, Northern Health Melbourne; Leni Soriano

Moderator: Prof Leo Celi

5.10 - 5.50
Panel Discussion: The Risk of Not Sharing Data

Dr Judy Gichoya,  Emory University; Dr David Pilcher, ANZICS; Torleif Lunde, University of Bergen; Trixie Tiangco, Cancer CARE Registry and Research Philippines Foundation

Moderator: Prof Ngiam Kee Yuan

5.50 - 6.00
Closing Remarks

SHADE22 co-chairs: A/Prof Ngiam Kee Yuan and Asst/Prof Feng Mengling