Tech Reduces Heart Test Results from 24 Hours to 5 Minutes
AI is improving dozens of new technologies for the medical field and healthcare around the world each year, from reading test results to spotting abnormalities on scans and x-rays with nearly perfect scores. Now doctors can detect a particular type of heart failure threat from a single heartbeat with 100% accuracy using convolutional neural networks.
That’s according to a recent study published in Biomedical Signal Processing and Control Journal, which explores how emerging technology can improve existing methods of detecting congestive heart failure.
While many diseases affect the heart, CHF affects nearly 5 million people in the U.S.
Nicholas Fearn’s story on forbes.com about this breakthrough reports that researchers at the Universities of Surrey, Warwick and Florence, have shown that AI can quickly and accurately identify CHF by analyzing one electrocardiogram (ECG) heartbeat.
Dr. Sebastiano Massaro, associate professor of organizational neuroscience at the University of Surrey, said:
“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.”
The speed at which these CNNs can review and discern the data is the most important advancement that AI can make for the doctors treating heart patients today. It’s clear that time is of the essence in 99% of people having heart issues of any kind.
Fearn further explained that unlike existing methods that are often time-consuming and inaccurate, their model combines advanced signal processing and machine learning tools on raw ECG signals to improve detection rates dramatically.
read more at forbes.com
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