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An Artificial Intelligence Algorithm for Detection of Severe Aortic Stenosis
15
Zitationen
4
Autoren
2024
Jahr
Abstract
Background: Identifying individuals with severe aortic stenosis (AS) at high risk of mortality remains challenging using current clinical imaging methods. Objectives: The purpose of this study was to evaluate an artificial intelligence decision support algorithm (AI-DSA) to augment the detection of severe AS within a well-resourced health care setting. Methods: using minimal input data (excluding left ventricular outflow tract measures) was applied to routine transthoracic echocardiograms (TTE) reports from 31,141 U.S. Medicare beneficiaries at an academic medical center (2003-2017). Results: (21.9%). Conclusions: Without relying on left ventricular outflow tract measurements, an AI-DSA used echocardiographic reports to reliably identify the phenotype of severe AS. These results suggest possible utility for this AI-DSA to enhance detection of severe AS individuals at risk for adverse outcomes.
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