how weak supervision can train deep learning models using unlabeled cardiac MRI sequences/videos

Key idea: use Snorkel to transform cardiologist domain knowledge into labeling functions --simple rules which capture information about our task-- to take advantage of the massive scale of unlabeled imaging data available in biobank.

This lets us rapidly build training sets for classification tasks such as bicuspid aortic valve, where a Snorkel-based approach improved our end model F1 performance by 64%.

This lets us rapidly build training sets for classification tasks such as bicuspid aortic valve, where a Snorkel-based approach improved our end model F1 performance by 64%.
https://www.nature.com/articles/s41467-019-11012-3

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