Assessing the severity of positive valence symptoms in initial psychiatric evaluation records: Should we use convolutional neural networks?-Reference-Cited by-同舟云学术

Assessing the severity of positive valence symptoms in initial psychiatric evaluation records: Should we use convolutional neural networks?

Published:2018-10-16 Issue:10 Volume:13 Page:e0204493
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Dai Hong-Jie^ORCID,Jonnagaddala Jitendra^ORCID

Funder

Ministry of Science and Technology, Taiwan (TW)

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference45 articles.

1. The global prevalence of common mental disorders: a systematic review and meta-analysis 1980–2013;Z Steel;International journal of epidemiology,2014

2. Mortality in mental disorders and global disease burden implications: a systematic review and meta-analysis;ER Walker;JAMA psychiatry,2015

3. The NIMH research domain criteria (RDoC) project: precision medicine for psychiatry;TR Insel;American Journal of Psychiatry,2014

4. Research Domain Criteria: cognitive systems, neural circuits, and dimensions of behavior;SE Morris;Dialogues Clin Neurosci,2012

5. 2016 CEGS NGRID Shared Tasks and Workshop on Challenges in Natural Language Processing for Clinical Data;O Uzuner,2016

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