Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

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Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Electronic medical record (EMR) offers promises for novel analytics. However, manual feature engineering from EMR is labor intensive because EMR is complex – it contains temporal, mixed-type and multimodal data packed in irregular episodes. We present a computational framework to harness EMR with mi...

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Bibliographic Details
Main Authors:	Tran, The Truyen, Nguyen, T., Phung, D., Venkatesh, S.
Format:	Journal Article
Published:	Academic Press Inc. 2015
Online Access:	http://hdl.handle.net/20.500.11937/23215

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