AI Model IDs Congestive Heart Failure from Single Heartbeat

An artificial intelligence (AI) neural network identified congestive heart failure with 100% accuracy, according to the findings of a study published in Biomedical Signal Processing and Control Journal. Just one raw electrocardiogram (ECG) heartbeat was what the AI needed to identify the condition, according to the paper. "Enabling clinical practitioners to access an accurate (congestive heart failure) detection tool can make a significant societal impact, with patients benefiting from early and more efficient diagnosis and easing pressures on (National Health Service) resources," said Leandro Pecchia, Ph.D., assistant professor of biomedical engineering at the University of Warwick in England. Typical congestive heart failure detection methods focus on heart variability and are time consuming and prone to errors, according to researchers. Instead, the research team developed a model which uses a combination of advanced signal processing and machine-learning tools on raw ECG signals.