New AI neural network approach detects heart failure from a single heartbeat with 100% accuracy

#artificialintelligence

Researchers have developed a neural network approach that can accurately identify congestive heart failure with 100 percent accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat, a new study reports. Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and sustained healthcare costs, clinical practitioners and health systems urgently require efficient detection processes. Dr. Sebastiano Massaro, associate professor of organizational neuroscience at the University of Surrey, has worked with colleagues Mihaela Porumb and Dr. Leandro Pecchia at the University of Warwick and Ernesto Iadanza at the University of Florence, to tackle these important concerns by using Convolutional Neural Networks (CNN) – hierarchical neural networks highly effective in recognizing patterns and structures in data. Published in the Biomedical Signal Processing and Control Journal, their research drastically improves existing CHF detection methods typically focused on heart rate variability that, whilst effective, are time-consuming and prone to errors.


AI Model IDs Congestive Heart Failure from Single Heartbeat

#artificialintelligence

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.


AI detects heart failure with 100% accuracy - Express Computer

#artificialintelligence

With the help of Artificial Intelligence(AI), researchers have developed a neural network approach that can accurately identify congestive heart failure with 100 per cent accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat. Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and sustained healthcare costs, clinical practitioners and health systems urgently require efficient detection processes. The researchers have worked to tackle these important concerns by using Convolutional Neural Networks (CNN) – hierarchical neural networks highly effective in recognising patterns and structures in data. "We trained and tested the CNN model on large publicly available ECG datasets featuring subjects with CHF as well as healthy, non-arrhythmic hearts. Our model delivered 100 per cent accuracy: by checking just one heartbeat we are able detect whether or not a person has heart failure," said study researcher Sebastiano Massaro, Associate Professor at the University of Surrey in the UK.


AI detects congestive heart failure with one heartbeat

#artificialintelligence

A new study has reported success in identifying severe heart failure in 100% of cases using a single heartbeat recording from an electrocardiogram (ECG). Medically, the condition called congestive heart failure (CHF) refers to a chronic loss of pumping power in the heart which is progressive. It is fairly common, causes significant illness and disability, and pushes up the costs of medical care. It affects about 26 million people around the world, and is more common in the elderly. It causes a considerable number of deaths, with about 40% mortality among the most severe cases.


AI Can Detect Heart Failure With 100% Accuracy By Hearing Just A Single Heartbeat

#artificialintelligence

In the recent past, it's become easier to detect heart conditions with technology. The Apple Watch has become pretty good at detecting arrhythmia for instance. But some researchers have been developing AI to detect heart problems, and one team may have the best version yet. According to a recent study published in the Biomedical Signal Processing and Control Journal, a team of researchers from the Universities of Surrey, Warwick and Florence have a new neural network that can detect cardiac anomalies from a single heartbeat with 100% accuracy. Their AI can quickly and accurately detect congestive heart failure (CHF) by analyzing one heartbeat on an electrocardiogram (ECG).