Machine Learning models have been deployed across many different aspects of society,
often in situations that affect social welfare. Although these models offer streamlined …

Artificial intelligence has a huge array of current and potential applications in healthcare and
medicine. Ethical issues arising due to algorithmic biases are one of the greatest challenges …

Decision-making systems based on AI and machine learning have been used throughout a
wide range of real-world scenarios, including healthcare, law enforcement, education, and …

Accumulating evidence demonstrates the impact of bias that reflects social inequality on the
performance of machine learning (ML) models in health care. Given their intended …

Population and public health are in the midst of an artificial intelligence revolution capable of
radically altering existing models of care delivery and practice. Just as AI seeks to mirror …

Artificial Intelligence (AI) consists of a range of sophisticated computational techniques,
encompassing machine learning algorithms and natural language processing among …

Background While artificial intelligence (AI) offers possibilities of advanced clinical
prediction and decision-making in healthcare, models trained on relatively homogeneous …

Diagnosing bias in data-driven algorithms for healthcare | Nature Medicine Skip to main
content Thank you for visiting nature.com. You are using a browser version with limited support …

As more researchers have become aware of and passionate about algorithmic fairness,
there has been an explosion in papers laying out new metrics, suggesting algorithms to …

The use of artificial intelligence (AI) in healthcare has the potential to improve patient
outcomes and increase efficiency in the delivery of care. However, the design, deployment …