Computer Learns How to Diagnose Patients

Computer Learns How to Diagnose Patients

Reported September 14, 2009

(Ivanhoe Newswire) — Mayo Clinic researchers say their new “teachable” software system mimics the human brain and may help diagnose cardiac infections without an invasive exam.

Developers call their program “artificial neural network” (ANN) because it mimics the brain’s cognitive function and reacts differently to situations depending on its accumulated knowledge. In this case, the ANN underwent three training sessions to learn how to evaluate numerous symptoms it would be considering.

ANN’s focus is to diagnose endocarditis, an infection in the heart’s valves or chambers. Endocarditis is serious and deadly for patients with implanted medical devices, killing as many as one in every five even with aggressive treatment and device removal. Diagnosis is invasive and risky, inserting a probe down the esophagus.


ANN tested 189 Mayo Clinic patients with device-related endocarditis diagnosed between 1991 and 2003. The best trained ANN correctly diagnosed 72 of 73 implant-related infections and 12 of 13 endocarditis cases.

Developers hope ANN will save patients from needless invasive procedures, avoiding the discomfort, risks and costs.

SOURCE: Presented at the Interscience Conference on Antimicrobial Agents and Chemotherapy (ICAAC) in San Francisco, September 12, 2009