Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …

With the broader and highly successful usage of machine learning (ML) in industry and the
sciences, there has been a growing demand for explainable artificial intelligence (XAI) …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …

In recent years, machine learning (ML) has become a key enabling technology for the
sciences and industry. Especially through improvements in methodology, the availability of …

Current learning machines have successfully solved hard application problems, reaching
high accuracy and displaying seemingly intelligent behavior. Here we apply recent …

Deep neural networks have led to state-of-the-art results in many medical imaging tasks
including Alzheimer's disease (AD) detection based on structural magnetic resonance …

There have been multiple recent proposals on using deep neural networks for code search
using natural language. Common across these proposals is the idea of embedding code …

Purpose We present image classifiers based on Dense Convolutional Networks and transfer
learning to classify chest X-ray images according to three labels: COVID-19, pneumonia …

The emerging field of eXplainable AI (XAI) in the medical domain is considered to be of
utmost importance. Meanwhile, incorporating explanations in the medical domain with …