Clinical medicine requires the integration of various forms of patient data including
demographics, symptom characteristics, electrocardiogram findings, laboratory values …

Myocarditis is a cardiovascular disease characterised by inflammation of the heart muscle
which can lead to heart failure. There is heterogeneity in the mode of presentation …

Quantification of myocardial scar from late gadolinium enhancement (LGE) cardiovascular
magnetic resonance (CMR) images can be facilitated by automated artificial intelligence (AI) …

Background There is an urgent need to find an effective and accurate method for triaging
coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore …

Background and objective Training convolutional neural networks based on large amount of
labeled data has made great progress in the field of image segmentation. However, in …

Left Ventricle (LV) detection from Cardiac Magnetic Resonance (CMR) imaging is a
fundamental step, preliminary to myocardium segmentation and characterization. This paper …

Left ventricular ejection fraction (LVEF) is the most important clinical parameter of
cardiovascular function. The accuracy in estimating this parameter is highly dependent upon …

Large datasets are often beneficial for the generation of predictive models using machine
learning approaches. However, it is often the case that not all variables in the dataset …

Artificial intelligence (AI) is transforming cardiovascular imaging by offering advancements
across multiple modalities, including echocardiography, cardiac computed tomography …

pyFUME is a python package for the automatic estimation of fuzzy inference systems. Fuzzy
models are considered among the most interpretable, understandable, and transparent …