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Rima Arnaout, an assistant professor, and cardiologist at UC San Francisco, is working on her research in computational medicine; she published a new study in the journal Digital Medicine. In the study, Arnaout and her colleagues used deep learning, specifically something called a convolutional neural network (CNN), to train an Artificial Intelligence system that can classify echocardiograms.
The system is created to analyze heart scan, that is just a simple task. The system is to outperform the human cardiologists but not to replace them.
It was a limited task, she notes, just the first step in what a cardiologist does when evaluating an echocardiogram (the image produced by bouncing sound waves off the heart). “The best technique is still inside the head of the trained echocardiographer,” she says.
The AI only performed this first step in the analysis of a heart image and the making of a diagnosis. A human cardiologist looks at many of these scans to examine more than 20 structures within the heart, then synthesizes that information to arrive at a conclusion.
Due to the complex structure of the heart, The first task of the cardiologist is to analyze the position of the images it is taken from. A cardiologist analyzes the images and high-resolution videos and based on the analysis they make some recommendations.
But the AI had a much harder task. It was given still images taken from video clips, and the images were shrunken down to just 60 by 80 pixels each.
The best part is, when AI and human cardiologists asked to sort these images into 15 categories of views, the AI achieved an accuracy of 92 percent. The humans got only 79 percent correct.
“These were excellent echocardiographers,” Arnaout says, “but it’s a hard task. We’re not used to seeing the images shrunken down and out of context.”
“A human echocardiographer can look at any heart, no matter what the defect, and figure out what’s going on,” Arnaout says. “I’m interested in building a platform that can do that.”
Arnaout is now working on a new version of the technology that can take the next steps to identify different diseases and heart problems.
Source: IEEE Spectrum