A deep learning model that uses a single chest X-ray to predict the 10-year risk of death from a heart attack or stroke, stemming from atherosclerotic cardiovascular disease has been developed by researchers. Results of the study were presented today (November 29) at the annual meeting of the Radiol
Deep learning is an advanced type of artificial intelligence that can be trained to search X-ray images to find patterns associated with disease.
“Based on a single existing chest X-ray image, our deep learning model predicts future major adverse cardiovascular events with similar performance and incremental value to the established clinical standard.” —This risk is calculated using the atherosclerotic cardiovascular disease risk score, a statistical model that considers a host of variables, including age, sex, race, systolic blood pressure, hypertension treatment, smoking, Type 2 diabetes, and blood tests.
“We’ve long recognized that X-rays capture information beyond traditional diagnostic findings, but we haven’t used this data because we haven’t had robust, reliable methods,” Dr. Weiss said. “Advances in AI are making it possible now.” The researchers also compared the prognostic value of the model to the established clinical standard for deciding statin eligibility. This could be calculated in only 2,401 patients due to missing data in the electronic record. For this subset of patients, the CXR-CVD risk model performed similarly to the established clinical standard and even provided incremental value.
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