Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

Journal: Journal of biomedical informatics

Published Date: May 12, 2017

Abstract

BACKGROUND: The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task.

Authors

Anthony Rios

Department of Computer Science, University of Kentucky, 329 Rose Street, Lexington, KY 40506, USA. Electronic address: anthony.rios1@uky.edu.
Ramakanth Kavuluru

Div. of Biomedical Informatics, Dept. of Internal Medicine, Dept. of Computer Science, University of Kentucky, Lexington, KY.

Keywords

Humans Neural Networks, Computer Neuropsychological Tests Severity of Illness Index

External Resources

View on PubMed Access via DOI PubMed (28506904)

Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

Abstract

Authors

Keywords

External Resources

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