Applying deep neural networks to unstructured text notes in electronic medical records for phenotyping youth depression.

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Applying deep neural networks to unstructured text notes in electronic medical records for phenotyping youth depression.

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Applying deep neural networks ...... phenotyping youth depression.

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Applying deep neural networks ...... phenotyping youth depression.

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Applying deep neural networks ...... phenotyping youth depression.

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P1476

Applying deep neural networks ...... phenotyping youth depression.

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Anvesh Roy

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James L Kennedy

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John Strauss

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Joseph Geraci

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Pamela Wilansky

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Vincenzo de Luca

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P2860

Automated de-identification of free-text medical records.

Extracting information from the text of electronic medical records to improve case detection: a systematic review

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Surveying Recent Themes in Translational Bioinformatics: Big Data in EHRs, Omics for Drugs, and Personal Genomics

Identification of Adverse Drug Events from Free Text Electronic Patient Records and Information in a Large Mental Health Case Register

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources

Developing a new model for patient recruitment in mental health services: a cohort study using Electronic Health Records

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.

A fast learning algorithm for deep belief nets.

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scholarly article

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10.1136/EB-2017-102688

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English

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2017-07-24T00:00:00Z

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28739578

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deep learning

deep neural network

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5566092

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