Pneumonia Detection on Chest X-ray Images Using Ensemble of Deep Convolutional Neural Networks

Pneumonia is a life-threatening lung infection resulting from several different viral infections. Identifying and treating pneumonia on chest X-ray images can be difficult due to its similarity to other pulmonary diseases. Thus, the existing methods for predicting pneumonia cannot attain substantial levels of accuracy. This paper presents a computer-aided classification of pneumonia, coined Ensemble Learning (EL), to simplify the diagnosis process on chest X-ray images. Our proposal is based on Convolutional Neural Network (CNN) models, which are pretrained CNN models that have been recently employed to enhance the performance of many medical tasks instead of training CNN models from scratch. We propose to use three well-known CNNs (DenseNet169, MobileNetV2, and Vision Transformer) pretrained using the ImageNet database. These models are trained on the chest X-ray data set using fine-tuning. Finally, the results are obtained by combining the extracted features from these three models during the experimental phase. The proposed EL approach outperforms other existing state-of-the-art methods and obtains an accuracy of 93.91% and a F1-score of 93.88% on the testing phase.

Advanced practices: micro learning, practice oriented teaching and gamified learning

The development, introduction and evaluation of ICT based techniques have been at the forefront of educational reform of all levels for the last two decades. Microlearning, gamified learning are two novel ICT techniques most appropriate for e-learning material and programs which attracted renewed attention because of the CoVID-19 social distancing measures. Alongside those, the more established technique of practice-oriented learning is being revisited to adapt to the new challenges. This article presents the main results and conclusions of deliverable 3.1. of the ERASMUS+ Capacity Building for Higher Education project "Electrical Energy Markets and Engineering Education (ELEMEND)" which is devoted to training partner staff in micro learning, practice oriented teaching and gamified learning. After the goals of ELEMEND are presented in the light of modern engineering education, the concept of micro learning as a training paradigm is discussed. Next, gamification technology is described in view of its role in the educational process and specific implementation examples are given. Finally, the practice-oriented approach both in teaching and in learning with the methods used to carry on this approach is presented.