Researchers have found a new approach to incorporating the larger web of relevant data for predictive modeling for individual and community health outcomes. In the U.S., the place where one was born, ...

AI bias is an anomaly in the output of machine learning algorithms. These could be due to the prejudiced assumptions made during the algorithm development process or prejudices in the training data.

AI ethics is a sub-field of applied ethics, focusing on the ethical issues raised by the development, deployment and use of AI. Its central concern is to identify how AI can advance or raise concerns ...

The specificity of the Perl-based algorithms was consistently high, over 98%. Very few benign results were classified as malignant or in situ by the Perl-based algorithms; the leukemia algorithm ...

Artificial intelligence (AI) algorithms have become integral to our modern lives, influencing everything from online ads to recommendations on streaming platforms. While they may not be inherently ...