359 citations · 359 across the 1 of their papers we have counts for
5 papers
Extracting possibly representative COVID-19 Biomarkers from X-Ray images with Deep Learning approach and image data related to Pulmonary Diseases
Ioannis D. Apostolopoulos, Sokratis Aznaouridis, Mpesiana Tzani
In this study, the problem of automatically classifying pulmonary diseases, including the recently emerged COVID-19, from X-Ray images, is considered. While the spread of COVID-19…
Non-invasive modelling methodology for the diagnosis of Coronary Artery Disease using Fuzzy Cognitive Maps
Ioannis Apostolopoulos, Peter Groumpos
Cardiovascular Diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Cor…
Investigating the Synthetic Minority class Oversampling Technique (SMOTE) on an imbalanced cardiovascular disease (CVD) dataset
Ioannis D. Apostolopoulos
In this work, we employ the Synthetic Minority Oversampling Technique (SMOTE) to generate instances of the minority class of an imbalanced Coronary Artery Disease dataset. We first…
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks
Ioannis D. Apostolopoulos, Tzani Bessiana
In this study, a dataset of X-Ray images from patients with common pneumonia, Covid-19, and normal incidents was utilized for the automatic detection of the Coronavirus. The aim of…
Experimenting with Convolutional Neural Network Architectures for the automatic characterization of Solitary Pulmonary Nodules' malignancy rating
Ioannis D. Apostolopoulos
Lung Cancer is the most common cause of cancer-related death worldwide. Early and automatic diagnosis of Solitary Pulmonary Nodules (SPN) in Computer Tomography (CT) chest scans ca…