Analyzing electronic health records can be a fast and accurate way to predict risk of death from COVID-19

Head shot of Estiri_Hossein

Hossein Estiri, PhD, is lead author on a study that utilized artificial intelligence to leverage the data compiled in electronic health records to compute individual-level risk scores for death after a COVID-19 infection. Among those predictors at the top of the list for those between the ages of 45-65 were age, history of pneumonia, diabetes (with complications), and cancer (breast and prostate). Learn more about the findings of this study in this piece on

“The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.”

Study authors: Hossein Estiri, Zachary H. Strasser, Jeffy G. Klann, Pourandokht Naseri, Kavishwar B. Wagholikar & Shawn N. Murphy