Scientists have built an artificial intelligence model to flag if previously unknown human genetic mutations are likely to cause disease, potentially transforming possibilities for the treatment of rare conditions. The technique draws on evolutionary information from hundreds of thousands of mainly animal species and outperforms rivals including Google DeepMind’s AlphaMissense, the researchers said. The innovation promises to offer doctors extra data to tackle medical problems they have never seen and may even be genetically unique in their origins. Rare diseases are estimated to affect hundreds of millions of people worldwide in aggregate, but many sufferers are never diagnosed. “There’s many ways in which single genetic variants can give rise to disease — and for this very large number of patients there’s often a terrible scarcity of information out there,” said Jonathan Frazer, a researcher at the Centre for Genomic Regulation in Barcelona.

Full research : Researchers detail popEVE, an AI model to predict the disease-causing potential of unknown human genetic mutations, and says it beats Google’s AlphaMissense.