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


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."

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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

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