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Blinded, randomized trial of sonographer versus AI cardiac function assessment

Bryan He, Alan C. Kwan, Jae Hyung Cho, Neal Yuan, Charles Pollick, Takahiro Shiota, Joseph Ebinger, Natalie A. Bello, Janet Wei, Kiranbir Josan, Grant Duffy, Melvin Jujjavarapu, Robert Siegel, Susan Cheng (), James Y. Zou () and David Ouyang ()
Additional contact information
Bryan He: Stanford University
Alan C. Kwan: Cedars-Sinai Medical Center
Jae Hyung Cho: Cedars-Sinai Medical Center
Neal Yuan: San Francisco VA, UCSF
Charles Pollick: Cedars-Sinai Medical Center
Takahiro Shiota: Cedars-Sinai Medical Center
Joseph Ebinger: Cedars-Sinai Medical Center
Natalie A. Bello: Cedars-Sinai Medical Center
Janet Wei: Cedars-Sinai Medical Center
Kiranbir Josan: Cedars-Sinai Medical Center
Grant Duffy: Cedars-Sinai Medical Center
Melvin Jujjavarapu: Cedars-Sinai Medical Center
Robert Siegel: Cedars-Sinai Medical Center
Susan Cheng: Cedars-Sinai Medical Center
James Y. Zou: Stanford University
David Ouyang: Cedars-Sinai Medical Center

Nature, 2023, vol. 616, issue 7957, 520-524

Abstract: Abstract Artificial intelligence (AI) has been developed for echocardiography1–3, although it has not yet been tested with blinding and randomization. Here we designed a blinded, randomized non-inferiority clinical trial (ClinicalTrials.gov ID: NCT05140642; no outside funding) of AI versus sonographer initial assessment of left ventricular ejection fraction (LVEF) to evaluate the impact of AI in the interpretation workflow. The primary end point was the change in the LVEF between initial AI or sonographer assessment and final cardiologist assessment, evaluated by the proportion of studies with substantial change (more than 5% change). From 3,769 echocardiographic studies screened, 274 studies were excluded owing to poor image quality. The proportion of studies substantially changed was 16.8% in the AI group and 27.2% in the sonographer group (difference of −10.4%, 95% confidence interval: −13.2% to −7.7%, P

Date: 2023
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DOI: 10.1038/s41586-023-05947-3

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