More accurate measurement of blood pressure

Dr Dean Picone, University of Tasmania

2020 Postdoctoral Fellowship

Years funded: 2021-2022

Cuff measured blood pressure is one of the most important tests in all clinical medicine. However, cuff blood pressure is not accurate in many individuals, and this can increase the likelihood of avoidable cardiovascular events (heart attack, stroke, kidney failure) through incorrect diagnosis and inappropriate medical care. This research program seeks to address this problem by developing and validating a more accurate way to measure cuff blood pressure using modern statistical techniques (machine learning). Using high-quality clinical data from 300 individuals and advanced blood pressure modelling approaches, I will develop machine learning algorithms for accurate blood pressure measurement. This is a world-first project that brings leading researchers in blood pressure and computational biology to solve a problem that has alluded scientists for decades. The primary outcome of a more accurate blood pressure method has immense significance because it will lead to better diagnosis and medical care of people, to reduce global death and illness from cardiovascular disease.