To determine whether an integrated AI decision support can save time and improve the accuracy of detection of intracardiac thrombus, the investigators are conducting a blinded, randomized controlled study of AI-guided detection of intracardiac thrombus to electrophysiologist judgment in preliminary readings of echocardiograms.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
1,500
A deep learning model will identify the intracardiac thrombus. The AI model will produce an assessment of intracardiac thrombus using video based features.
Cardiac electrophysiologists use their own experience to determine whether there is intracardiac thrombus
Shanghai Chest Hospital
Shanghai, Shanghai Municipality, China
Degree of change from initial (AI vs EP doctor) assessment to final cardiologist assessment
Time frame: 10 Minutes
Perioperative adverse event rates
Time frame: 10 Minutes
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