Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

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, ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...

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

Artificial intelligence (AI) has become part of the daily lexicon, and an endless stream of media reports assert that AI either has affected or will affect most aspects of human life. What is AI and ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

In a new study published in Nature titled, “Custom CRISPR-Cas9 PAM variants via scalable engineering and machine learning,” researchers from Massachusetts General Hospital (MGH) and Harvard Medical ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...