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 optimisation of process planning has emerged as a pivotal aspect of modern manufacturing, where genetic algorithms (GAs) and hybrid techniques are leveraged to address the combinatorial complexity ...

Artificial intelligence (AI) is transforming every aspect of our lives. Humans can now reduce complex and mundane tasks while focusing on core working requirements, significantly increasing workforce ...

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 ...