Researchers have demonstrated a new technique that allows "self-driving laboratories" to collect at least 10 times more data ...

Using these insights, the team developed a machine learning model incorporating 13 predictors, achieving high accuracy in predicting gene selection across programs.

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

When Anomalo’s co-founders left Instacart in 2018, they thought they could put machine learning to work to solve data-quality problems inherent in large datasets. Five years later, the company ...

They also found that their machine learning model correctly predicted the behavior of the proteins in macaque monkeys even though it was trained only on mouse and human cell data.

In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators ...

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

When it comes to vehicle testing and validation, nothing we’ve encountered before comes close to the complexity of autonomous ...

Research team creates statistical model to predict COVID-19 resistance Proof-of-concept study shows promise for machine-learning system that uses electronic health data to make its predictions ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited ...