RESUMO
Tissue loss in the forearm is a common entity. There are various etiologies to tissue loss like trauma, burn, post-surgery, etc. Coverage of defect or tissue loss of the forearm is a surgical challenge and options available for forearm coverage are limited. To bypass this difficulty, McGregor pedicled groin flap is used by us to cover large forearm defects with successful outcomes in this case series.
RESUMO
COVID-19 is one of the biggest pandemics that the world is facing today, and every day, we are coming up with new challenges in this area. Still, much research is already going on to overcome this pandemic, and we also get succeeded to some extent. Diverse sources such as MRI, CT scanning, blood samples, X-ray image, and many more are available to detect COVID-19. Thus, it can be easily said that through image processing, the classification of COVID-19 can be done. In this study, the COVID-19 detection is done by classifying with the use of a type of convolutional neural network termed a detail-oriented capsule network. Chest CT scan imaging for the prediction of COVID-19 and non-COVID-19 are classified in the present paper using a Detailed Oriented capsule network (DOCN). Accuracy, specificity, and sensitivity are parameters used for model evaluation. The proposed model has achieved 98% accuracy, 81% sensitivity, and 98.4% specificity.
