With respect to artificial intelligence driven neural network, doctors will now be able to detect heart failures from a single heartbeat with 100% accuracy. The study was published in Biomedical Signal Processing and Control Journal and speaks about the technology in connection with detection of congestive heart failure. According to reports, the study was initiated by researchers of Universities of Surrey, Warwick and Florence and will use AI to identify CHF and will also analyze one electrocardiogram (ECG) heartbeat. According to experts, using convolutional neural networks (CNN) will help in identifying structures and pattern in data. The application of CNN will also be less time consuming in comparison to the existing methods which take a lot of time and are also often inaccurate. Reports allege, the model is a combination of machine learning tools and advanced signal processing. The tools are used on raw ECG signals and hence are also useful in improving the detection rates. “First, by assessing ECG directly, we confirm that with AI it is possible to accurately detect CHF looking beyond heart rate variability analysis. Thus, we have in general results that are more adherent to the real behavior of the affected heart,” commented Dr Sebastiano Massaro, associate professor of organizational neuroscience at the University of Surrey. In another part of the experiment, a CNN model was also used to improve the accuracy of CHF detection in addition to other comparable models. As reported by Massaro, futuristic study will extend to largescale samples and in other classes of CHF in order to help implement the technology in everyday healthcare systems and practices.
Tags : Artificial intelligence, Heart Failure, Massaro, CHF,