A small study shows artificial intelligence can pick out individuals with coronavirus infections, but ophthalmologists and AI experts say the approach is far from proven to be capable of distinguishing infections with SARS-CoV-2 from other ills.

The technology, tested out on patients with epilepsy who already had electrodes implanted in their brains, is currently limited to 30–50 sentences.

A deep neural network can help determine how likely cancer cells are to metastasize.

Scientists traced 1,000 neurons through the mouse brain, uncovering new details about how the organ is wired.

Microbiologist Nick Loman talks about the power of artificial intelligence and the best way to use it.

An artificial intelligence program called a neural network exceeds radiologists’ ability to detect malignancies, but more testing is needed before using the program clinically.

Neural networks generate abstract images designed to activate particular cells, lending insight into their function.

Marvin Minsky engineered the first known artificial neural network, in which “rats” represented as lights learned to solve a maze.

A brief history of AI, machine learning, artificial neural networks, and deep learning.

Artificially intelligent software has human-like ability to analyze host-pathogen interactions in microscopy images.

Neuromorphic technology is fueling fast, large-scale simulations, supporting researchers’ endeavors to build models of the human brain.

The drugs lead to widespread, predictable changes in brain waves that can help anesthesiologists personalize anesthesia and develop anesthetic-based treatments.

A new study uses deep learning to improve the resolution of biological images, but elicits skepticism about its ability to enhance snapshots of sample types that it has never seen before.

A deep learning program can identify cells with higher metastatic potential based on the way they look and move.

Researchers have created a 3D-printed artificial neural network that uses light photons to rapidly process information.

Machine-learning algorithms tuned to detecting cancer DNA in the blood could pave the way for personalized cancer care.

An algorithm trained to move through a virtual environment spontaneously generated patterns of activity found in so-called grid neurons.

A map of neural networks in the striatum of the mouse brain reveals clues about psychiatric and movement disorders.