The proof-of-concept study could be a step toward better assisted communication devices for paralyzed people.

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.

Double-strand breaks can produce several different outcomes.

The latest machine learning models can identify many visual and molecular features of a particular cancer. If the technology advances to the clinic, it could help diagnose patients and predict survival.

Machine learning can analyze photographs of cancer, tumor pathology slides, and genomes. Now, scientists are poised to integrate that information into cancer uber-models.

Machine learning could be the key to reducing the use of animals in experiments.

Researchers are using artificial intelligence to pick out the features of brightfield microscopy images.