Research: Machine Learning May Cut Pandemic Hospitalizations 30%

New research shows machine learning can be more effective than current methods to distribute scarce treatments to patients most vulnerable during a public health crisis

A new study sheds light on a promising approach using machine learning to more effectively allocate medical treatments during a pandemic or any time there's a shortage of therapeutics.

The findings, published today in JAMA Health Forum, found a significant reduction in expected hospitalizations when using machine learning to help distribute medication using the COVID-19 pandemic to test the model. The model proves to reduce hospitalizations relatively by 27 percent compared to actual and observed care.