Event

Health data is not exclusively useful for the field of #Medicine, but also #Artificial Intelligence, #Big Data, #Engineering, #Public Health and you name it! But how to get access to these vast and valuable data? Set up by Hospital Authority Data Collaboration Lab (HADCL), Self-service Data Platform serves to encourage innovative research ideas and collaborations using HA clinical data.

In this symposium, four distinguished CUHK researchers will share their insights of capitalizing on the health data supported by HADCL for their research, including:

• Machine Learning for Liver Cancer Prediction with Data from HADCL
• Collaboration between Physicians and Data Scientists in Utilizing HA Health data: An Experience Sharing
• Artificial Intelligence in MRI Radiology: Interaction between Data and Model Reliability
• Utilizing Hospital Authority Shared Data to Explore a Hypothesis for Grant Application: An Experience Sharing

Date: 6 Dec 2021 (Mon)
Time: 10:30 am – 12:30 pm
Venue: UGA, InnoPort
Language: English
Registration: click here (Deadline: 3 Dec 2021, 3 pm)

Speakers

Prof. Grace Wong Lai Hung
Professor Grace Wong is a Professor in the department of Medicine and Therapeutics at the Chinese University of Hong Kong. Prof. Wong’s main research interests include big data research in medicine, chronic viral hepatitis, liver fibrosis and liver cancer. She has published over 360 articles in peer-reviewed journals, and is currently the Director of CUHK Medical Data Analytics Centre (MDAC), the Editor-in-Chief of Hepatology (Hong Kong edition), and the Associate Editor for other academic journals. She has been awarded the Young Investigator Award of the Asian Pacific Association for the Study of the Liver in 2009, the Ten Outstanding Young Persons (TOYP) of Hong Kong in 2014, the Richard Yu Lectureship of the Hong Kong College of Physicians in 2021 and so forth.

Prof. Martin Wong Chi Sang
Professor Martin C. S. Wong is a specialist in Family Medicine and a researcher in the field of cancer screening and prevention of chronic diseases. Prof. Wong has composed over three hundred publications in international peer-reviewed journals, and received over 15 research awards for studies in his research area, including the prestigious “1st Distinguished Research Making Family Medicine Shine Award” by the World Organization of Family Doctors in 2018. In 2016, he was conferred as an Honorary Fellow by the Hong Kong Academy of Nursing to recognize his achievements in the profession and contributions to primary care. He was appointed as the Editor-in-Chief of the Hong Kong Academy of Medicine in 2017; and Fellows of various Academies, Royal Colleges and professional societies.

Dr. Matthew Wong Lun
Dr. Lun M. Wong is an academic specialized in analytical radiology research, specializing in artificial intelligence (AI). He obtained his PhD degree from the Department of Imaging and Interventional Radiology of The Chinese University of Hong Kong and is currently serving as a Research Assistant Professor in the same department. His research interest focused on investigating the applications of AI, including deep learning and radiomics, in managing cancers of the complex region of the head and neck. His major field of work involved tailoring artificial neural networks to detect, segment and characterize nasopharyngeal carcinoma on plain MRI sequences.

Prof. Marc Chong Ka Chun
Dr. Marc Chong is currently an Assistant Professor in the JC School of Public Health and Primary Care, the Chinese University of Hong Kong. Dr. Chong has worked as a biostatistician in the Centre for Clinical Research and Biostatistics since 2006, possessing rich experience in conducting various statistical analysis of academic and industrial clinical trials. He has also been a statistical consultant for different consultation projects, such as Development of Refined Population-based Model to Inform Resource Allocation, Surgical Outcomes Monitoring and Improvement Programme, and Intensive Care Units Outcomes Monitoring Program held by Hospital Authority.

Click here for the catalogue of the symposium.

Enquiry: InnoPort Team | Email: innoport@cuhk.edu.hk | Tel: +852 3943 0475