RSNA 2021 Imaging Informatics Preview

Prediction model forecasts need for COVID-19 resources

By Erik L. Ridley, AuntMinnie.com staff writer

Wednesday, December 1 | 1:30 p.m.-2:30 p.m. | SSMS05-5 | Room S405
In this talk, researchers will describe how data in the electronic medical record (EMR) can be used to predict if a COVID-19 patient will need to be admitted to the hospital.

Researchers led by Imon Banerjee, PhD, of Emory University and colleagues trained a machine-learning algorithm to predict a patient's need for hospitalization within seven days of a positive reverse transcription polymerase chain reaction (RT-PCR) test based on patient demographics, medication, past medical procedures, comorbidities, and laboratory results. The multimodal "fusion" AI model yielded a promising level of prediction performance -- an 84% overall F1 score.

"We conclude that fusion modeling using medical history and current treatment data can forecast the need for hospitalization for patients infected with COVID-19 at the time of the RT-PCR test," the authors wrote.

What else did they find? You'll have to attend this Wednesday afternoon presentation to learn more.


Last Updated er 11/18/2021 4:17:42 PM