To determine whether an integrated AI decision support can save time and improve accuracy of assessment of echocardiograms, the investigators are conducting a blinded, randomized controlled study of AI guided measurements of left ventricular ejection fraction compared to sonographer measurements in preliminary readings of echocardiograms.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
3,495
A semantic segmentation deep learning model will identify the left ventricle and label the left ventricle. The AI model will produce an assessment of LVEF using video based features.
Standard practice sonographer measurement of left ventricle and assessment of LVEF
Cedars-Sinai Medical Center
Los Angeles, California, United States
Frequency of >5% change in LVEF between preliminary and final report
Proportion of studies the LVEF is changed more than 5% in final report
Time frame: 10 Minutes
Average change in LVEF between preliminary and final report
Mean change in LVEF between preliminary and final report
Time frame: 10 Minutes
Frequency cardiologist adjusts preliminary annotation
Proportion of studies the annotation is changed
Time frame: 10 Minutes
Average change in LVEF between prior clinical report and final report
Mean change in LVEF between prior clinical report and final report
Time frame: 10 Minutes
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