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PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data
In this work, we present PheME, an Ensemble framework using Multi-modality data of structured EHRs and unstructured clinical notes for accurate Phenotype prediction.
Rectifying the Data Bias in Knowledge Distillation
In this paper, we first quantitatively define the uniformity of the sampled data for training, providing a unified view for methods that learn from biased data.
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