With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …

Automatically understanding the content of medical images and delivering accurate
descriptions is an emerging field of artificial intelligence that combines skills in both …

The ever-increasing amount of biomedical data is enabling new large-scale studies, even
though ad hoc computational solutions are required. The most recent Machine Learning …

Every year physicians face an increasing demand of image-based diagnosis from patients, a
problem that can be addressed with recent artificial intelligence methods. In this context, we …

Background A radiology report communicates the imaging findings to the referring clinicians.
The rising number of referrals has created a bottleneck in healthcare. Writing a report takes …

Although deep learning-based AI systems for diagnostic imaging tasks have virtually
showed superhuman accuracy, their use in medical settings has been questioned due to …

The application of deep convolutional neural networks (CNN) in the field of medical image
processing has attracted extensive attention and demonstrated remarkable progress. An …

The increasing demand for transparent and reliable models, particularly in high-stakes
decision-making areas such as medical image analysis, has led to the emergence of …

In recent years, machine learning for clinical decision support has gained more and more
attention. In order to introduce such applications into clinical practice, a good performance …

The interpretation of medical images is a fundamental process for the diagnosis and
treatment of patients. This process contributes determining the causes of symptoms as well …