Machine learning

By analysing heart cells, a new machine learning algorithm could help predict arrhythmia risk before symptoms appear.

Technology for finding non-visual defects in semiconductors leaps forward thanks to an online machine learning algorithm that learns on the fly.

Researchers develop machine learning models for accurately diagnosing an inflammatory skin condition.

Despite the hype, State-of-the-art machine learning challenges one of the toughest problems in systems biology.

Researchers build a state-of-the-art computational model that can identify emotional cues in real-life conversations

A new diagnostic innovation powered by artificial intelligence could empower surgeons to make more accurate and effective clinical decisions for colon cancer patients.

A new cloud-based machine learning framework processes sensitive encrypted data 20 times faster than its predecessors.

Artificial intelligence could help speed up the discovery and development of materials towards a greener future.

Researchers have built a navigation algorithm that leverages multidimensional real-world data to map faster and more efficient traffic routes.

To fully realise the potential of medical technology, A*STAR scholar Daryl Jude Lawrence explains why scientists should move beyond the lab and experience the inner workings of industry-level production and entrepreneurship.

A new compression method developed at A*STAR shrinks energy and hardware requirements for complex computational platforms on everyday devices.

A purpose-built machine learning platform takes the guesswork out of catalyst formulations for green energy generation.