Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

A novel machine learning version of the Opioid Risk Tool provides high precision screening for opioid use disorder in chronic pain patients.

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

Boardroom priorities are shifting from financial metrics toward technical oversight. Although market share and operational ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Quiq reports on the role of automation in customer service, highlighting tools like AI for questions, ticket classification, ...

Using detailed surveys and machine learning computation, new research co-authored at UC Berkeley's Center for Effective Global Action finds that eradicating extreme poverty would be surprisingly ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

Severe bleeding is one of the most common and preventable causes of death after traumatic injury, yet currently available tools have poor ability to determine which patients urgently need blood ...

If built, the 14-building complex would require 1,000 megawatts of power – or enough electricity to power roughly 500,000 homes. The amount of water the data center complex would need is less clear.