The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions

The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions

Major depressive disorder imposes a substantial disease burden worldwide, ranking as the third leading contributor to global disability. In spite of its ubiquity, classifying and treating depression has proven troublesome. One argument put forward to explain this predicament is the heterogeneity of...

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Bibliographic Details
Main Authors: Nick J. Ermers, Karin Hagoort, Floortje E. Scheepers
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Psychiatry
Subjects:
electronic health records
major depressive disorder
machine learning
natural language processing
precision psychiatry
predictive modeling
Online Access:https://www.frontiersin.org/article/10.3389/fpsyt.2020.00472/full

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