New York: A team of researchers has used an Artificial Intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu. The researchers, including Pradipta Ghosh from the University of California San Diego, indicated two telltale signatures. One, a set of 166 genes, reveals how the human immune system responds to viral infections. A second set of 20 signature genes predicts the severity of a patient's disease. For example, the need to hospitalise or use a mechanical ventilator.

Washington: Gene expression patterns associated with pandemic viral infections provide a map to help define patients' immune responses, measure disease severity, predict outcomes and test therapies, for current and future pandemics. Researchers at the University of California San Diego School of Medicine used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data, which genes are "on" or "off" during infection and to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu. Two telltale signatures emerged from the study, published in eBiomedicine called "AI-guided discovery of the invariant host response to viral pandemics". One, a set of 166 genes, reveals how the human immune system responds to viral infections. The second set of 20 signature genes predicts the severity of a patient's disease.