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Found 3 papers, 2 papers with code
Semi-Supervised Multimodal Multi-Instance Learning for Aortic Stenosis Diagnosis
However, existing deep learning pipelines for assessing AS from echocardiograms have two key limitations.
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning
To automate screening for AS, deep networks must learn to mimic a human expert's ability to identify views of the aortic valve then aggregate across these relevant images to produce a study-level diagnosis.
Fix-A-Step: Semi-supervised Learning from Uncurated Unlabeled Data
Semi-supervised learning (SSL) promises improved accuracy compared to training classifiers on small labeled datasets by also training on many unlabeled images.
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