Synthetic Healthcare Data: Privacy, Algorithm, and Application in Hong Kong

We are stepping into an era of personalized healthcare, in which healthcare is increasingly tailored to an individual’s unique genetic profile and care needs. The ambition of personalized healthcare requires and has generated an unprecedented amount of sensitive clinicogenomic data to advance research and health services. A central dilemma for policymakers, industry partners, health providers and researchers alike has been how to accelerate these advancements by sharing data while still safeguarding patient’s privacy.

Synthetic data generation, a critical development in data science and artificial intelligence, has the potential to significantly mitigate patient privacy concerns in data sharing while maintaining research value. This modeling technique generates a new dataset with the same statistical properties as the original dataset, but does not compromise the privacy of individuals. Demonstration projects have been undertaken in several industries such as banking and healthcare.

A diversity of audience will find this cross-disciplinary event insightful. No matter whether you are a government official, health administrator, physician, AI enthusiast, biotech veteran, entrepreneur, compliance officer, social scientist or law student, we look forward to exchanging ideas with you in the event. See you there!

Speakers :

Mr. Gareth Lane, Lead, Personalized Health Care, Roche

Prof. Wilson Wong, Co-Director, Data Science and Policy Studies, The Chinese University of Hong Kong; CASBS Fellow, Stanford University

Ms. Marta Batlle López, Data Scientist at Roche (remote)

Ms. Jennifer Leung, Manager, STP Platform