Machine learning systems can help humans to make decisions by providing
...
Models trained with empirical risk minimization (ERM) are known to learn...
Interpretable part-prototype models are computer vision models that are
...
Automatically summarizing radiology reports into a concise impression ca...
Part-prototype models are explainable-by-design image classifiers, and a...
Supervised machine learning utilizes large datasets, often with ground t...
The goal of Explainable AI (XAI) is to design methods to provide insight...
The rising popularity of explainable artificial intelligence (XAI) to
un...
AI/Computing at scale is a difficult problem, especially in a health car...
Interpretable machine learning addresses the black-box nature of deep ne...
Image recognition with prototypes is considered an interpretable alterna...
Over the last years, threat intelligence sharing has steadily grown, lea...
Unstructured information in electronic health records provide an invalua...
Machine learning systems have become popular in fields such as marketing...
Semantic annotations have to satisfy quality constraints to be useful fo...