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Home Health

Digital solutions for heart failure patients

by Francesco Mazzagatti
August 29, 2021
in Health
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Delegates also heard from Professor Declan O’Regan (Imperial College London), who spoke of future precision phenotyping and risk prediction in cardiomyopathy, and the added value that machine learning can bring to every stage of cardiovascular imaging. ‘That starts from the point of image acquisition and reconstruction, to image enhancement like super resolution, to labelling images, and also identifying pathology and new imaging biomarkers of disease, such as the concept of radiomics, and also moving beyond conventional diagnosis towards prediction tasks, which really drives management decisions in the clinic.’ O’Regan covered three main topics – how computational imaging can be useful in cardiovascular medicine, ranging from integrating data, and bringing imaging and non-imaging data together; using AI and imaging for discovery science and understanding new mechanisms of heart disease; and for early diagnosis and risk prediction.

Finally, on the vexing issue of overload, Professor Tim Chico (University of Sheffield), questioned and suggested how to cope with the amount of data being generated a in his presentation ‘A cardiovascular digital twin; the brain assist device we need to make sense of data overload?’

Profile:

Dr Fozia Ahmed is a consultant cardiologist at the Manchester Heart Centre, part of Manchester Royal Infirmary, where she specialises in heart failure and cardiac devices. In December 2020 she received a major UK award for her outstanding contribution to heart failure services and excellence in HF care. Her research interests include risk prediction models, remote monitoring in heart failure, and prevention of cardiovascular infection; with a focus on re-designing clinical pathways to improve patient outcomes.

Source: Healthcare in Europe

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