Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MS

• Published in: PloS one Vol. 17; no. 7; p. e0263954
• Main Authors: Rashidi, Hooman H., Pepper, John, Howard, Taylor, Klein, Karina, May, Larissa, Albahra, Samer, Phinney, Brett, Salemi, Michelle R., Tran, Nam K.
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 29.07.2022; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Automation; Biology and life sciences; Computer and Information Sciences; Coronaviruses; COVID-19; COVID-19 vaccines; Datasets; Evaluation; Infectious diseases; Innovations; Learning algorithms; Machine learning; Mass spectrometry; Mass spectroscopy; Medical tests; Medicine and Health Sciences; Pandemics; Physical Sciences; Platforms; Public health; Research and Analysis Methods; Severe acute respiratory syndrome; Severe acute respiratory syndrome coronavirus 2; Spectroscopy; Viral diseases; United States

The 2019 novel coronavirus infectious disease (COVID-19) pandemic has resulted in an unsustainable need for diagnostic tests. Currently, molecular tests are the accepted standard for the detection of SARS-CoV-2. Mass spectrometry (MS) enhanced by machine learning (ML) has recently been postulated to...