Artificial intelligence or machine learning was found to help identify which infants with fever are at a low risk for a serious bacterial infection.

‘Fever in young infants is very common, but only about 10 percent turn out to have a serious bacterial infection, such as urinary tract infection, bacterial meningitis, or bacteremia (bacteria in the blood). ’

However, using the available decision rules to determine risk produces too many false positives, meaning that those infants undergo invasive procedures, receive antibiotics and might be hospitalized unnecessarily. 




In the study, among 1,240 patients who received a lumbar puncture, the artificial intelligence model could have prevented 849 (over 68 percent) of such procedures. The model produced results with both high sensitivity (accurate detection of true positives) and specificity (accurate detection of true negatives).
"It may still take many years before artificial intelligence algorithms become standard practice in medicine," says Dr. Ramgopal. "It is an exciting area of research with great potential to improve care of our patients."
Source-Eurekalert