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

Professor Kelvin KF Tsoi, a Digital Epidemiologist, Research Associate Professor, Stanley Ho Big Data Decision Analytics Research Centre, at the Chinese University of Hong Kong will speak on machine learning classification on blood pressure variability in this lunchtime seminar.

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.