IRC Seminar: "Machine Learning Classification on Blood Pressure Variability: from SPRINT to Community eHealth Program in Hong Kong".

Time: 13:00-14:00

Lunch: 12:30

Location: G10, Henley Business School, Whiteknights

Registration: Free

Presenter: Prof. Kelvin KF Tsoi, Associate Professor, JC School of Public Health and Primary Care

Introduction:

Hypertension has long been considered a modifiable major risk factor of cardiovascular diseases. However, visit-to-visit blood pressure variability (BPV) has recently been gaining attention and studies have suggested that it is independent of blood pressure (BP) and associated with cardiovascular risks. However, many aspects of BPV such as measurement frequency and interaction with drugs remain unclear. In this work, we would begin by presenting our post hoc analysis on BPV based on SPRINT trial. This is followed by a discussion on a community-based BP-monitoring programme, named eHealth, as a way forward to our SPRINT study.

Abstract Machine Learning Classification On Blood Pressure Variability From Sprint Trial To Community E Health Program In Hong Kong

Bio

Prof. Kelvin KF Tsoi

Digital Epidemiologist, Research Associate Professor, Stanley Ho Big Data Decision Analytics Research Centre

The Jockey Club School of Public Health and Primary Care, The Jockey Club Institute of Ageing, The Chinese University of Hong Kong

President, the International Society of Digital Health, Associate Editor, BMJ Innovations,

Minitrack Chair, Big Data on Healthcare Application, HICSS

Dr. Kelvin Tsoi is an Epidemiologist and a Data Scientist. He received his Bachelor degree in Statistics and Doctoral degree in Medical Sciences in the Chinese University of Hong Kong. He also received clinical research training in the Department of Medicine and Therapeutics, and was responsible for the colorectal cancer prevention project. Before his current position, he worked as a research scientist in the statistical department of Hospital Authority (HA). He led projects covering a wide range of challenging areas on chronic diseases, such as service demand projection for schizophrenia and dementia. The experience of database management enhanced his understanding of the HA database structures and also the potential research topics.

His research focus is on Digital Health, which is the application of real-time mobile or social digital data for improving public health or reducing future disease burden. The application of Artificial Intelligent on Big Data research is also my interest. Our recent research covers digital dementia screening and machine learning on blood pressure variability. He has published over 50 full scientific articles in the foremost journals. A recent paper to compare dementia screening was published in JAMA Internal Medical. His work on Big Data was published in the Institute of Electrical and Electronics Engineers (IEEE) international conferences.

PRESENT APPOINTMENTS

PUBLICATIONS

Selected Publications on Hypertension:

• Tsoi KK, Wong MC, Tam WW, Hirai HW, Lao XQ, Wang HH, Kwan MW, Cheung CS, Tong EL, Cheung NT, Yan BP, Meng HM, Griffiths SM. Cardiovascular mortality in hypertensive patients newly prescribed perindopril vs. lisinopril: a 5-year cohort study of 15,622 Chinese subjects. Int J Cardio 2014;176:703-9.
• Yip B, Hirai HW, Kuo YH, Meng HM, Wong S, Tsoi K. Blood Pressure Management with Data Capturing in the Cloud among Hypertensive Patients - A Monitoring Platform for Hypertensive Patients, In Proceedings of IEEE BigData Congress 2015.
• Tsoi KK, Kuo YH, Meng HM. A Data Capturing Platform in the Cloud for Behavioral Analysis Among Smokers - An Application Platform for Public Health Research, In Proceedings of IEEE BigData Congress 2015.
• Tsoi KK, Yip B, Au DW, Kuo YH, Wong SY, Woo J, Meng HM. Blood Pressure Monitoring on the Cloud System in Elderly Community Centres: A Data Capturing Platform for Application Research in Public Health. In Proceedings of the 7^th International Conference on Cloud Computing and Big Data 2016.
• Tsoi KK, Lam MW, Chan FC, Hirai H, Bat BK, Wong SY, Meng HM. Classification of Visit-to-Visit Blood Pressure Variability: A Machine Learning Approach for Data Clustering on Systolic Blood Pressure Intervention Trial (SPRINT). In Proceedings of the 7^th Digital Health Conference 2017.

Other Selected Publications:

• Tsoi KKF, Chan JYC, Hirai HW, Wong SYS, Kwok TCY. Cognitive tests to detect dementia: A systematic review and meta-analysis. JAMA Intern Med 2015;175:1450-1458.
• Tsoi KK, Chan NB, Chan FC, Zhang L, Lee AC, Meng HM. How can we better use Twitter to find a person who got lost due to Dementia? NPJ Digital Medicine 2018;1:14.