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

Our brains have evolved to the point where we can build artificial brains that might help us understand our brains. Let that sink in.

The Carnegie Mellon computational biologist thinks machine learning algorithms can direct high-throughput experiments to solve the field’s unanswered questions.

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.

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

Machine learning algorithms predict the repairs made to DNA after Cas9 cuts.

Algorithms for motion capture help neuroscientists dig into the question of how the brain produces behavior.

A high school student designs a new beehive and gets help from machine learning to monitor for varroa mite infestation.

Researchers are developing computational approaches to extract information from multiple sets of single-cell sequencing data.

AI models can pick up subtle alterations in linguistic and vocal attributes of spoken language that may be indicative of failing health.

The Yale University cognitive neuroscientist studies how the brain extracts patterns from experiences.