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Mayo Clinic AI Software Helps Diagnose Endocarditis


The Artificial Neural Network mimics cognitive brain function and reacts to accumulated knowledge. Evaluating data from 189 patients, the system correctly identified 72 of 73 implant-related infections and 12 of 13 endocarditis cases.

Researchers from the Mayo Clinic have developed software that is designed to mimic the human brain and assist physicians in diagnosing cardiac infections without an invasive exam.

According to a Mayo Clinic news release, researchers there have developed an “artificial neural network” (ANN) that “mimics the brain’s cognitive function and reacts differently to situations depending on its accumulated knowledge” and “trained it” to learn how to evaluate the symptoms of endocarditis.

Study author M. Rizwan Sohail, MD, an infectious diseases specialist at the Mayo Clinic, said that if the software works as hoped, it can be used to “help determine a percentage of endocarditis diagnoses with a high rate of accuracy,” thus saving “a significant number of patients from the discomfort, risk, and expense of the standard diagnostic procedure.”

During the study, the research team used the ANN to evaluate data from 189 patients with device-related endocarditis. The system correctly identified 72 of 73 implant-related infections and 12 of 13 endocarditis cases, with a confidence level greater than 99 percent, inpatients with a known diagnosis of endocarditis. The news release also notes that “when used on an overall sample that included both known and unknown cases, the ANN accurately excluded endocarditis in at least half of the cases, thus eliminating half the cohort from a needless invasive procedure.”

Results from this study were presented Saturday at the Interscience Conference on Antimicrobial Agents and Chemotherapy in San Francisco.

More about Artificial Neural Networks and Artificial Intelligence in Healthcare

This archive of past and current Artificial Intelligence computer systems used in clinical practice, compiled by Open Clinical, offers information on acute care systems, decision support systems, educational systems, laboratory systems, medical imaging software, and systems used for quality assurance and administration.

Open Clinical also offers this brief review of the use of artificial neural networks in healthcare

“Overview of Artificial Neural Networks and their Applications in Healthcare” provides “an overview of the basics of neural networks, their operation, major architectures that are widely employed for modeling the input-to-output relations, and the commonly used learning algorithms for training the neural network models.” It also briefly outlines several of the “major application areas of neural networks for the improvement and well-being of human health.”

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