For example, ArchaicSeeker 2.0 analyses have identified repeated episodes of both Neanderthal and Denisovan introgression in contemporary human populations with regional patterns of archaic ...

"Our goal was to identify the presence of glial cells in synaptic transmission using different machine-learning methods, which do not require strong assumptions about the data," said Pena. "We ...

Unsupervised machine learning: On the other hand, in unsupervised learning, the model is trained using non-labeled data and predicts output on its own based on hidden patterns.

Beneath Yellowstone’s stunning surface lies a hyperactive seismic world, now better understood thanks to machine learning.

Automatic Process Exploration through Machine Learning Assisted Transition State Searches. Physical Review Letters, 2025; 134 (9) DOI: 10.1103/PhysRevLett.134.096201 ...

Deep learning, a computer program that mimics the learning process of our brains, enabled the team to analyze the large amounts of data they collected to find patterns in the responses. By ...

Led by researchers at NYU Langone Health, the new study used an AI technique called machine learning to analyze thousands of MRI brain scans from 471 men and 560 women.

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by ...

A new Apple-backed AI model trained on Apple Watch behavioral data can now predict a wide range of health conditions more ...

APE separates process exploration from kMC simulations, using fuzzy machine-learning classification to identify distinct atomic environments. This allows for a broader exploration of potential ...