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Deep Learning to Predict Patient Future Diseases from the Electronic Health Records

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)

Abstract

The increasing cost of health care has motivated the drive towards preventive medicine, where the primary concern is recognizing disease risk and taking action at the earliest stage. We present an application of deep learning to derive robust patient representations from the electronic health records and to predict future diseases. Experiments showed promising results in different clinical domains, with the best performances for liver cancer, diabetes, and heart failure.

Keywords

Disease prediction Preventive medicine Electronic health records Medical information retrieval Deep learning 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkUSA

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