Coronavirus patient Khomeini Hospital

Investigators at NYU’s Grossman Scholl of Medicine used artificial intelligence to analyze the biomarkers and records of patients at two Chinese hospitals who had COVID-19—and to predict which of those patients would develop acute respiratory disease.  “The researchers were surprised to find that characteristics considered to be hallmarks of COVID-19, like certain patterns seen in lung images (e.g. ground glass opacities), fever, and strong immune responses, were not useful in predicting which of the many patients with initial, mild symptoms would go to develop severe lung disease. Neither were age and gender helpful in predicting serious disease, although past studies had found men over 60 to be at higher risk.  Instead, the new AI tool found that changes in three features – levels of the liver enzyme alanine aminotransferase (ALT), reported myalgia, and hemoglobin levels – were most accurately predictive of subsequent, severe disease. Together with other factors, the team reported being able to predict risk of ARDS with up to 80 percent accuracy.” MORE

Image Credit:   Wikimedia.commons

Key words: COVID-19, acute respiratory disease, biomarkers, artificial intelligence, predictive diagnosis, New York University, Wenzhou Central Hospital, Cangnan People’s Hospital