Machine learning to predict cardiovascular events and response to therapy based on echocardiographic-derived functional and morphological characteristics of the heart. KU Leuven
Cardiovascular disease remains a major health problem worldwide, as it is responsible for about 30% of all deaths. When diagnosing the heart, ultrasonic imaging remains the modality of choice not only due to the fact that it is non-invasive, mobile and relatively cheap but also because it can generate images in real-time and at a high rate (e.g. conventionally about 30 images/second can be generated). Although worldwide a lot of research ...