Addressing racial and phenotypic bias in human neuroscience methods
Despite their premise of objectivity, neuroscience tools for physiological data collection,
such as electroencephalography and functional near-infrared spectroscopy, introduce racial …
such as electroencephalography and functional near-infrared spectroscopy, introduce racial …
Algorithmic fairness in computational medicine
Machine learning models are increasingly adopted for facilitating clinical decision-making.
However, recent research has shown that machine learning techniques may result in …
However, recent research has shown that machine learning techniques may result in …
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
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 …
of clinical experts. However, in settings differing from those of the training dataset, the …
[图书][B] More than a glitch: Confronting race, gender, and ability bias in tech
M Broussard - 2023 - books.google.com
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 …
redesign our systems to create a more equitable world. The word “glitch” implies an …
Decaf: Generating fair synthetic data using causally-aware generative networks
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 …
training data. Instead of solving for this by introducing fair learning algorithms directly, we …
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
Robust and efficient medical imaging with self-supervision
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" …
clinical expert level performance. However, such systems tend to demonstrate sub-optimal" …
[HTML][HTML] A healthy debate: Exploring the views of medical doctors on the ethics of artificial intelligence
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 …
that, while there is great promise in the implementation of AI technologies in healthcare, it …
Synthetic generation of face videos with plethysmograph physiology
Accelerated by telemedicine, advances in Remote Photoplethysmography (rPPG) are
beginning to offer a viable path toward non-contact physiological measurement …
beginning to offer a viable path toward non-contact physiological measurement …
Incorporating physics into data-driven computer vision
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 …
Although images are formed through the physics of light and mechanics, computer vision …