Johns Hopkins University (JHU) researchers have received a $195,000 Rapid Response Research grant from the National Science Foundation to use machine learning to identify the risk of adverse cardiac events in Covid-19 patients.

JHU professor of biomedical engineering Natalia Trayanova said: “This project will provide clinicians with early warning signs and ensure that resources are allocated to patients with the greatest need.”

The data of more than 300 Covid-19 patients will be collected, including electrocardiograms (ECGs), cardiac-specific laboratory data, continuously-obtained vital signs like heart rate and oxygen saturation, and imaging data such as computed tomography (CT) scans and echocardiography.

This data will then be used to train the team’s algorithm, with the hope that it will then be able to create a predictive risk score that can determine which patients are at risk of developing adverse cardiac events.