An advanced artificial intelligence (AI) model can scan short audio clips for signs of valvular heart disease (VHD), bringing a whole new meaning to the phrase “listen to your heart.”
The full analysis was published in IEEE Transactions on Biomedical Engineering.[1]
“Most cases of VHD are missed because of human error—so we brought in AI to help the human,” principal investigator Negar Ebadi, an associate professor of electrical and computer engineering at Stevens Institute of Technology in New Jersey, said in a prepared statement.
“In the realm of healthcare, the limitations of standard stethoscope examinations are evident,” added lead author Arash Shokouhmand, a recent Stevens graduate. “It is imperative that we invest in advanced diagnostic tools to bridge this gap and ensure early detection and treatment for all patients.”
Noting that primary care physicians are typically unable to consistently detect signs of heart murmurs with a stethoscope, the researchers thought they could use AI to improve patient outcomes by a significant margin. They tested that theory by training an AI model to process 10-second bursts of audio data from a person’s chest and alert the user when relevant findings were identified.
The algorithm was tested 58 VHD patients and an additional 52 healthy patients, achieving a sensitivity of 93%, specificity of 98%, accuracy of 97% and positive predictive value of 93%. In fact, the group added, their AI model can identify up to five different valvular diseases from a single 10-second burst of sound.
“Our ability to detect multiple diseases simultaneously was a key innovation in this research,” Shokouhmand said. “We aren’t just showing that there’s a valvular problem — we’re able to identify the constellation of problems a patient is suffering from.”
The researchers are far from done exploring the possibilities of this advanced algorithm. They are currently gathering more data with a long-term goal of being able to classify diseases by their severity.
“Instead of showing that you have a particular valvular disorder, we could give a grade out of 10 describing how far the disease has progressed,” Ebadi explained.
Click here to read the full study in IEEE Transactions on Biomedical Engineering.
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.