Abstract
Marfan syndrome is diagnosed by aortic enlargement, which can lead to complications such as aortic dilation, aortic dissection, and even rupture of the aortic wall in extreme cases. As part of this work, we developed a CNN system whose function is to interpret chest X-ray images and determine whether they show an enlarged aorta. Two architectures were studied for best hyper-parameters that affect the performance of DenseNet and Inception-v3. In most tests, the system obtained high accuracy rates, low loss rates, and no overfitting, making it a valuable tool for medical practitioners to help provide an initial diagnosis to potential patients.
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