Research in computer analysis of medical images bears many promises to improve patients'
health. However, a number of systematic challenges are slowing down the progress of the …

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

A plethora of work has shown that AI systems can systematically and unfairly be biased
against certain populations in multiple scenarios. The field of medical imaging, where AI …

How does the accuracy of deep neural network models trained to classify clinical images of
skin conditions vary across skin color? While recent studies demonstrate computer vision …

Abstract Domain generalization is a ubiquitous challenge for machine learning in
healthcare. Model performance in real-world conditions might be lower than expected …

Abstract Machine learning brings the hope of finding new biomarkers extracted from cohorts
with rich biomedical measurements. A good biomarker is one that gives reliable detection of …

This paper proposes a deep learning method for low-light image enhancement, which
exploits the generation capability of Neural Networks (NNs) while requiring no training …

Many works have shown that deep learning-based medical image classification models can
exhibit bias toward certain demographic attributes like race, gender, and age. Existing bias …

Deep learning algorithms have demonstrated remarkable efficacy in various medical image
analysis (MedIA) applications. However, recent research highlights a performance disparity …

In recent years, numerous dermatological image databases have been published to make
possible the development and validation of artificial intelligence-based technologies to …