AI-Assisted Heart Ultrasound Decision-Making: Promising for Less Experienced Clinicians
Brief news summary
During the ESC Congress 2024, a trial was conducted to compare the efficiency of artificial intelligence (AI) with current methods in identifying patients with suspected heart disease. The trial employed AI software called EchoGo Pro, which interprets stress echocardiography (SE) images, a common diagnostic test for coronary artery disease. Patients were randomly assigned to receive either standard clinical decision-making or AI-assisted decision-making. The results showed that although AI did not perform as well as clinical decision-making in selecting patients for invasive procedures and predicting acute coronary events, it showed promise in improving decision-making for less-experienced clinicians and in complex scenarios. The researchers concluded that AI has the potential to enhance the accuracy and consistency of stress echocardiogram interpretations, regardless of clinician experience.A randomized trial found that the use of artificial intelligence (AI) to assist in clinical decision-making for heart ultrasounds is not significantly different from current practices in identifying patients with suspected heart disease who may benefit from invasive investigation and treatment. However, the study showed that AI improved decision making for less-experienced clinicians and had promising results in clinically complex sub-groups. The integration of AI in healthcare holds promise for faster and more accurate diagnosis, according to lead author Dr. Ross Upton from the University of Oxford.
The study enrolled patients referred to stress echocardiography (SE) clinics for assessment of suspected coronary artery disease (CAD). The AI software, EchoGo Pro, provided automated interpretation of SE images to clinicians. While AI did not demonstrate non-inferiority to clinical decision-making overall, it showed potential benefits for less-experienced clinicians and in challenging diagnostic scenarios.
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AI-Assisted Heart Ultrasound Decision-Making: Promising for Less Experienced Clinicians
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