Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about. (For more background, check out our first flowchart ...

Researchers at Princeton and the Simons Foundation turned the traditional approach on its head, teaching a machine learning algorithm to look for the genetic relationships that could cause autism.

Perhaps that should have been more obvious from the start, since people have been building various machine learning algorithms ... Sellier] is using a genetic algorithm to work within the confines ...

Machine learning is hard. Algorithms in a particular ... To do this, AutoML-Zero uses what are known as genetic algorithms, which have been around since the 1980s, but have fallen out of use ...

When DNA's double helix is broken after damage from, say, exposure to X-rays, molecular machines perform a kind of genetic "auto ... By creating a machine-learning algorithm that predicts how ...

Perhaps that should have been more obvious from the start, since people have been building various machine learning algorithms ... Sellier] is using a genetic algorithm to work within the confines ...

In a paper appearing in Bioinformatics, researchers combined machine-learning with a genetic algorithm to overcome the limitations of existing methods. The team, including Trisevgeni Rapakoulia of the ...

Polygenic risk scores, or PRS, reflect a person's genetic susceptibility to a particular disease ... which people are now questioning. With AI and machine learning algorithms, you have to be really ...