acm-header
Sign In

Communications of the ACM

ACM TechNews

Algorithm Accurately Detects Disease-Causing Variants in Infants with Rare Diseases


View as: Print Mobile App Share: Send by email Share on reddit Share on StumbleUpon Share on Hacker News Share on Tweeter Share on Facebook

Said Fabric Genomics CEO Martin Reese, "Finally, clinicians do not have to sacrifice accuracy for speed when faced with a possible rare disease diagnosis in a critical setting like the NICU (newborn intensive care unit), where time is of the essence."

Credit: Timofeev Vladimir

Researchers at the biotechnology firm Fabric Genomics and the Rady Children's Institute for Genomic Medicine found that the Fabric GEM artificial intelligence algorithm detected disease-causing variants in infants with rare diseases at six leading genomic centers and hospitals with high accuracy.

In conjunction with whole-genome and whole-exome data, the algorithm ranked the causative variant first or second over 90% of the time.

Rady's Dr. Stephen Kingsmore said, "Fast and definitive genetic diagnosis is essential to providing the right treatment in a timely manner for critically ill newborns. Fabric GEM has successfully demonstrated that it can automatically and quickly suggest a very short list of candidate genes for interpretation through whole-genome or whole-exome sequencing."

From News-Medical Life Sciences
View Full Article

 

Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

No entries found