Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample

Abstract

BACKGROUND Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self… (More)
DOI: 10.1371/journal.pone.0167055

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Cite this paper

@inproceedings{Dipnall2016IntoTB, title={Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample}, author={Joanna F. Dipnall and Julie A Pasco and Michael Berk and Lana J. Williams and Seetal Dodd and Felice N. Jacka and Denny Meyer}, booktitle={PloS one}, year={2016} }