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

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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 detects heart failure with 100% accuracy - Express Computer

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

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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).


Apple Watch detects heart problem known to cause strokes

Daily Mail - Science & tech

The Apple Watch has been found to detect a heart condition that affects some 2.7 million people in the US, a new study has revealed. By pairing the smartwatch's heart rate sensors with artificial intelligence, researchers developed an algorithm capable of distinguishing an irregular heartbeat, known as atrial fibrillation, from a normal heart rhythm - and with 97 percent accuracy. Atrial fibrillation, although easily treatable, has been difficult to diagnose and the team believes their work could pave the way for new methods to identify the abnormality. The Apple Watch has been found to detect a heart condition that affects some 2.7 million people in the US, a new study has revealed. The algorithm was accurate 97 percent of the time using the smartwatch's heart rate sensor (stock) University of California, San Francisco, in collaboration with the app Cardiogram, trained a deep neural network with heart readings from 6,158 Cardiogram users.


Apple Watch 97% Accurate In Diagnosing Irregular Heartbeat, Study Says

International Business Times

Apple Watch might be more than a fancy accessory for your wrist. The device could be of great help to heart patients, according to a'Health e-heart' study conducted by University of California, San Francisco, which finds that the device is 97 percent accurate in diagnosing irregular heartbeat. "Our results show that common wearable trackers like smartwatches present a novel opportunity to monitor, capture and prompt medical therapy for atrial fibrillation without any active effort from patients. While mobile technology screening won't replace more conventional monitoring methods, it has the potential to successfully screen those at an increased risk and lower the number of undiagnosed cases of AF," the report's senior author, Gregory M. Marcus, MD, MAS Endowed Professor of Atrial Fibrillation Research and Director of Clinical Research for the Division of Cardiology at UCSF, said in the findings published Wednesday. The research trained a deep neural network (DNN) and paired it with the Apple Watch and Cardiogram app.