A Deep Learning Ensemble Approach for Automated COVID-19 Detection from Chest CT Images.

BACKGROUND: The aim of this study was to evaluate the performance of an automated COVID-19 detection method based on a transfer learning technique that makes use of chest computed tomography (CT) images. METHOD: In this study, we used a publicly available multiclass CT scan dataset containing 4171 CT scans of 210 different patients. In particular, we extracted features from the CT images using a set of convolutional neural networks (CNNs) that had been pretrained on the ImageNet dataset as feature extractors, and we then selected a subset of these features using the Information Gain filter. The resulting feature vectors were then used to train a set of k Nearest Neighbors classifiers with 10-fold cross validation to assess the classification performance of the features that had been extracted by each CNN. Finally, a majority voting approach was used to classify each image into two different classes: COVID-19 and NO COVID-19. RESULTS: A total of 414 images of the test set (10% of the complete dataset) were correctly classified, and only 4 were misclassified, yielding a final classification accuracy of 99.04%. CONCLUSIONS: The high performance that was achieved by the method could make it feasible option that could be used to assist radiologists in COVID-19 diagnosis through the use of CT images.

Non Vitamin K Antagonist Oral Anticoagulants in Atrial Fibrillation Patients Scheduled for Electrical Cardioversion: A Real-Life Propensity Score Matched Study.

AIM: The aim of the present study was to assess the safety and effectiveness of non-vitamin K antagonist oral anticoagulants (NOACs) versus vitamin K antagonists (VKAs) in atrial fibrillation (AF) patients undergoing electrical cardioversion (EC). METHODS: A propensity score-matched analysis was performed in order to identify two homogeneous groups including AF patients on NOACs and VKAs treatment scheduled for EC. The primary safety endpoint was major bleeding. The composite of stroke, transient ischemic attack (TIA) and systemic embolism (SE) was the primary effectiveness endpoint. The discontinuation rate of anticoagulant therapy was assessed. RESULTS: A total of 495 AF patients on NOACs therapy and scheduled for EC were compared to 495 VKAs recipients. No statistically significant differences in the incidence of both major bleeding (1.01% versus 1.4%; P= 0.5) and thromboembolic events (0.6% versus 0.8%; P= 0.7) were observed during a mean follow-up of 15 ± 3 months. The discontinuation rate of NOACs was significantly lower compared to VKAs (1.6% versus 3.6%, P=0.04). CONCLUSION: We showed a safe and effective clinical profile of NOACs among AF patients scheduled for electrical cardioversion in real-life setting. Patients on NOACs therapy showed a lower discontinuation rate compared to those on VKAs.