Extended Data Fig. 1: Hyperparameter search for spatiotemporal convolutions on the video dataset to predict ejection fraction.

Model architecture (R2+1D, which is the architecture selected by EchoNet-Dynamic for ejection fraction prediction, R3D and MC3), initialization (solid line, Kinetics-400 pretrained weights; dotted line, random initial weights), clip length (1, 8, 16, 32, 64, 96 and all frames) and sampling period (1, 2, 4, 6 and 8) were considered. a, When varying clip lengths, performance is best at 64 frames (corresponding to 1.28 s) and starting from pretrained weights improves performance slightly across all models. b, Varying sampling period with a length to approximately correspond to 64 frames before subsampling. Performance is best with a sampling period of 2.