An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

• Published in: Human genomics Vol. 17; no. 1; p. 80
• Main Authors: Charkoftaki, Georgia, Aalizadeh, Reza, Santos-Neto, Alvaro, Tan, Wan Ying, Davidson, Emily A, Nikolopoulou, Varvara, Wang, Yewei, Thompson, Brian, Furnary, Tristan, Chen, Ying, Wunder, Elsio A, Coppi, Andreas, Schulz, Wade, Iwasaki, Akiko, Pierce, Richard W, Cruz, Charles S Dela, Desir, Gary V, Kaminski, Naftali, Farhadian, Shelli, Veselkov, Kirill, Datta, Rupak, Campbell, Melissa, Thomaidis, Nikolaos S, Ko, Albert I, Thompson, David C, Vasiliou, Vasilis
• Format: Journal Article
• Language: English
• Published: England BioMed Central 29.08.2023; BMC
• Subjects: Accuracy; Allantoin; Biomarkers; Comorbidity; COVID-19; COVID-19 - epidemiology; Datasets; Discriminant analysis; Disease; Disease Outbreaks; Epidemics; Hospitalization; Hospitals; Humans; Infections; Leukocytes (eosinophilic); Machine Learning; Mechanical ventilation; Metabolism; Metabolites; Metabolomics; Outbreaks; Patients; Plasma; Prediction models; Serotonin; Severe acute respiratory syndrome coronavirus 2; Triage; Tryptophan; Uric acid; White people

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utiliz...