Machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients based on multimodal echocardiographic parameters

2024-04-12 cardiovascular medicine Title + abstract only

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BACKGROUNDAlthough clinical prediction models have been proposed to predict thrombosis risk in non-valvular atrial fibrillation (NVAF), machine learning (ML) based models to predict thrombotic risk were limited. This study aimed to develop a robust ML-based predictive model that integrates multimodal echocardiographic data and clinical risk factors to evaluate the risk of thrombosis in patients with NVAF. METHODS AND RESULTSA total of 402 NVAF patients scheduled for AF radiofrequency ablation a...

Machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients based on multimodal echocardiographic parameters

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