In a development set of 290 245 transthoracic echocardiographic videos across the Yale–New Haven Health System (YNHHS), we used augmentation approaches, and a customised loss function weighted for view quality to derive a POCUS-adapted, multi-label, video-based convolutional neural network that discriminates hypertrophic cardiomyopathy and transthyretin amyloid cardiomyopathy from controls without known disease. Here, TTR is linked to cardiac amyloidosis.