The biomarker, known as CXCL10, “could help to drastically reduce the number of samples needing to be sequenced in order to detect new viral infections,” the Yale Daily News, a student newspaper at New Haven, Conn.-based Yale University, reported Feb. 2.
Currently, three key methods for infectious pathogens exist, and the researchers’ study expands the scope of one of the three.
As part of their methodology, researchers utilized machine learning technology to analyze the various levels of the CXCL10 biomarker in those who were infected versus those who were not and discovered “a significant difference between CXCL10 levels in patients who tested positive for viral infections and those who did not.”
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