Using AI analysis of ultrasound heart scans, the team will seek to identify the markers of heart failure and develop an image analysis risk prediction model, which can be used by doctors. It will use the AI engine from Ultromics’ first product, EchoGo Core, to analyse 10,000 echocardiograms, including assessment of systolic and diastolic information throughout the entire cardiac cycle.
Dr Ross Upton, CEO and co-founder of Ultromics, said: ‘This project is focused on a critical aspect of cardiac disease as it affects so many people every day. Using our pioneering AI technology stack, our objective is to map and scan databases of ultrasound images and develop detailed models to diagnose and hopefully even predict heart failure. Early intervention can make a huge difference to a patient’s treatment and quality of life – so the sooner we can identify the condition, the better.’
The research programme aims to develop a diagnostic and predictive tool that can rapidly identify heart failure, reduce misdiagnosis, and enable its earlier prevention, freeing up clinician time.
‘The study has two key objectives: the first is to identify novel biomarkers that can help identify early signs of heart failure. And the second is to develop a machine learning model using the novel biomarkers to provide an automated risk prediction of heart failure at the point of care,’ added Upton.