AI model achieves 89% accuracy in identifying arrhythmia-related abnormalities in atrial tissue
Researchers from the COR group at the Institute of Information and Communications Technologies (ITACA) of the Universitat Politècnica de València (UPV) have developed an artificial intelligence model capable of locating and quantifying tissue abnormalities associated with atrial cardiomyopathy using electrical recordings from the body's surface.
Researchers from the COR group at Spain's Universitat Politècnica de València have created an artificial intelligence model that can identify and measure abnormalities in heart tissue using surface electrical recordings. The graph neural network model achieved an 89% accuracy rate in pinpointing affected areas and 84% accuracy in assessing the extent of damage.
The study, published in Discover Computing, utilized simulated data in a proof-of-concept trial, meaning further clinical validation is necessary before any potential applications.
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