As artificial intelligence (AI) transitions from research to deployment, creating the appropriate
datasets and data pipelines to develop and evaluate AI models is increasingly the biggest …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Concept Bottleneck Models (CBMs) map the inputs onto a set of interpretable concepts
(``the bottleneck'') and use the concepts to make predictions. A concept bottleneck enhances …

Understanding the performance of machine learning models across diverse data
distributions is critically important for reliable applications. Motivated by this, there is a …

Deep learning models have achieved great success in automating skin lesion diagnosis.
However, the ethnic disparity in these models' predictions, where lesions on darker skin …

Background: While skin cancers are less prevalent in people with skin of color, they are
more often diagnosed at later stages and have a poorer prognosis. The use of artificial …

Deep Learning failure cases are abundant, particularly in the medical area. Recent studies
in out-of-distribution generalization have advanced considerably on well-controlled synthetic …

Early diagnosis plays a pivotal role in effectively treating numerous diseases, especially in
healthcare scenarios where prompt and accurate diagnoses are essential. Contrastive …

The use of machine learning models in high-stake applications (eg, healthcare, lending,
college admission) has raised growing concerns due to potential biases against protected …

In the past few years, there have been rapid advances in technology and the use of digital
tools in health care and clinical research. Although these innovations have immense …