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Synthesizing more realistic echocardiographic data lets deep learning models beat the clinical standard for myocardial strain estimation, a key biomarker for early diagnosis.
Reinforcement learning can now handle active feature selection in high-dimensional datasets by intelligently pruning the feature search space and regularizing decision sequences, outperforming existing methods in accuracy and policy complexity.
