Software may help diagnose cardiac infections

WASHINGTON, US: New research suggests that "teachable software", designed to mimic the human brain, may help diagnose cardiac infections in a non-invasive manner.

Endocarditis -- an infection involving the valves and sometimes chambers of the heart -- can be a problem in patients with implants. It is a serious condition and can be deadly.

The mortality rate can be as high as one in five, even with aggressive treatment and removal of the device. With additional complications, the mortality can shoot up to over 60 percent -- or more than one in two.

Diagnosis usually requires an invasive procedure that also has risks.

The software programme is called an "artificial neural network" (ANN) because it mimics the brain's cognitive function and reacts differently to situations depending on its accumulated knowledge.

That knowledge or training is provided by researchers, similar to how a person would "train" a computer to play chess, by introducing it to as many situations as possible.

In this case, the ANN underwent three separate "trainings" to learn how to evaluate the symptoms it would be considering.

"If, through this novel method, we can help determine a percentage of endocarditis diagnoses with a high rate of accuracy, we hope to save a significant number of patients from the discomfort, risk and expense of the standard diagnostic procedure," says M. Rizwan Sohail, leader of the study and Mayo Clinice, Minnesota, infectious diseases specialist.

The team studied 189 Mayo patients with device-related endocarditis diagnosed between 1991 and 2003.

The ANN was tested retrospectively on the data from these cases. When tested on cases with known diagnosis of endocarditis, the best-trained ANN was correct most of the time (72 of 73 implant-related infections and 12 of 13 endocarditis cases).

These findings were presented at the Interscience Conference on Antimicrobial Agents and Chemotherapy (ICAAC) in San Francisco.

© IANS