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- W2773841331 abstract "We consider the problem of predicting three procedures, viz, EKG, Angioplasty and Valve Replacement procedures jointly from Electronic Health Records (EHR) and develop a discriminative boosted Bayesian network algorithm. Differences between our proposed approach and standard Bayes Net structure learners are (1) we do not assume that the number of features (observations) are uniform across training examples and (2) our method explicitly handles the precision-recall tradeoff. Our empirical evaluations on a real EHR data demonstrates the superiority of this proposed approach to learning these procedures individually." @default.
- W2773841331 created "2017-12-22" @default.
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- W2773841331 date "2017-11-01" @default.
- W2773841331 modified "2023-09-23" @default.
- W2773841331 title "Discriminative boosted Bayes networks for learning multiple cardiovascular procedures" @default.
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- W2773841331 doi "https://doi.org/10.1109/bibm.2017.8217770" @default.
- W2773841331 hasPublicationYear "2017" @default.
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