The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized
biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre …

Semi-supervised learning (SSL) improves model generalization by leveraging massive
unlabeled data to augment limited labeled samples. However, currently, popular SSL …

Abstract Convolutional Neural Networks (CNNs) have advanced existing medical systems
for automatic disease diagnosis. However, there are still concerns about the reliability of …

Quantum physics has changed the way we understand our environment, and one of its
branches, quantum mechanics, has demonstrated accurate and consistent theoretical …

Recommender systems play a significant role in information filtering and have been utilized
in different scenarios, such as e-commerce and social media. With the prosperity of deep …

Driven by recent advances in Artificial Intelligence (AI) and Computer Vision (CV), the
implementation of AI systems in the medical domain increased correspondingly. This is …

Automated medical image analysis systems often require large amounts of training data with
high quality labels, which are difficult and time consuming to generate. This paper …

Since recent achievements of Artificial Intelligence (AI) have proven significant success and
promising results throughout many fields of application during the last decade, AI has also …