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Project

Machine learning for computer-aided diagnostics in echocardiography

Thanks to the evolution in computing power and digital storage space, machine learning has enabled finding complex patterns in huge data sets thereby bringing direct benefit to the society. Advances made in areas such as computer vision are now mature enough for transfer to medical imaging, where an enormous number of parameters determine the outcome of a patient. Some recent exploratory findings of the applicants confirm that machine learning can outperform experts in diagnostic reading of echocardiographic images. Within this project, a big database of well-labeled echocardiographic data will be constructed on which state-of-the-art learning methodologies will be applied in order to develop a computer-aided diagnostic system of the heart.
Date:1 Oct 2018 →  30 Sep 2020
Keywords:Cardiology, Diagnostics, Echocardiography, Computer-aided diagnostics, Machine learning
Disciplines:Cardiac and vascular medicine