Understanding metabolic processes through machine learning

Bioinformatics researchers at Heinrich Heine University Düsseldorf (HHU) and the University of California at San Diego (UCSD) are using machine learning techniques to better understand enzyme kinetics and thus also complex ...

The promise of the "learn to code" movement

This week, educators, students and the public around the world are participating in Computer Science Education Week by organizing and leading one-hour coding tutorials.

Smarter AI—machine learning without negative data

A research team from the RIKEN Center for Advanced Intelligence Project (AIP) has successfully developed a new method for machine learning that allows an AI to make classifications without what is known as "negative data," ...

Computing solutions for biological problems

Producing research outputs that have computational novelty and contributions, as well as biological importance and impacts, is a key motivator for computer scientist Xin Gao. His Group at KAUST has experienced a recent explosion ...

Quantum computers tackle big data with machine learning

Every two seconds, sensors measuring the United States' electrical grid collect 3 petabytes of data – the equivalent of 3 million gigabytes. Data analysis on that scale is a challenge when crucial information is stored ...

Painting a clearer picture of the heart with machine learning

Coronary artery disease (CAD) is a condition in which plaque forms on the walls of coronary arteries, causing them to narrow. Eventually, this could lead to a heart attack, or death. This condition is now the single largest ...

How to make computers faster and climate friendly

Your smartphone is far more powerful than the NASA computers that put Neil Armstrong and Buzz Aldrin on the moon in 1969, but it is also an energy hog. In computing, energy use is often considered a secondary problem to speed ...

Helping to improve medical image analysis with deep learning

Medical imaging creates tremendous amounts of data: many emergency room radiologists must examine as many as 200 cases each day, and some medical studies contain up to 3,000 images. Each patient's image collection can contain ...

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