Potential COVID-19 biomarkers identified through mass spectrometry and machine-learning algorithms

Written by Vivian Xie

Using mass spectrometry and machine learning, metabolomic studies were carried out to determine possible COVID-19 biomarkers to identify and assess the risk of developing severe illness. A team of researchers, led by Anderson Rocha and Rodrigo Catharino from the University of Campinas (São Paulo, Brazil), has conducted a study involving 442 patients who tested positive for COVID-19 with varying severities of symptoms, 350 patients who tested negative for COVID-19 – who functioned as controls – and 23 suspected COVID-19 cases, despite a negative COVID-19 test. Blood plasma samples from each participant were analyzed with mass spectrometry and machine-learning algorithms. From...

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