Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

Despite their premise of objectivity, neuroscience tools for physiological data collection,
such as electroencephalography and functional near-infrared spectroscopy, introduce racial …

Abstract Machine-learning models for medical tasks can match or surpass the performance
of clinical experts. However, in settings differing from those of the training dataset, the …

When technology reinforces inequality, it's not just a glitch—it'sa signal that we need to
redesign our systems to create a more equitable world. The word “glitch” implies an …

Abstract Machine learning models have been criticized for reflecting unfair biases in the
training data. Instead of solving for this by introducing fair learning algorithms directly, we …

Machine learning models are increasingly adopted for facilitating clinical decision-making.
However, recent research has shown that machine learning techniques may result in …

Video-based remote physiological measurement utilizes facial videos to measure the blood
volume change signal, which is also called remote photoplethysmography (rPPG) …

Recent progress in Medical Artificial Intelligence (AI) has delivered systems that can reach
clinical expert level performance. However, such systems tend to demonstrate sub-optimal" …

Artificial Intelligence (AI) is moving towards the health space. It is generally acknowledged
that, while there is great promise in the implementation of AI technologies in healthcare, it …

Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …