Corrigendum to "Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review." J Affect Disord. 241 (2018) 519-532.

J Affect Disord

Institute of Medical Science, University of Toronto, Toronto, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada; Brain and Cognition Discovery Foundation, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Pharmacology, University of Toronto, Toronto, Canada. Electronic address:

Published: September 2020

AI Article Synopsis

  • - The authors identified and corrected an error in the meta-analysis, changing the classification accuracy for Serretti et al. (2007) to 64%.
  • - Despite this correction, the overall results of the analysis remain consistent before and after the change.
  • - The authors apologized for any inconvenience this error may have caused.

Article Abstract

The authors regret an error in one of the extracted data points in the meta-analysis. The classification accuracy for Serretti et al. (2007) was corrected to 64% (Table 3b). The overall results before and after this correction remain directionally consistent and are summarized below (Figures 2 and 3; Table 2; results subsection 3.6). The authors apologise for any inconvenience caused.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jad.2020.02.037DOI Listing

Publication Analysis

Top Keywords

corrigendum "applications
4
"applications machine
4
machine learning
4
learning algorithms
4
algorithms predict
4
predict therapeutic
4
therapeutic outcomes
4
outcomes depression
4
depression meta-analysis
4
meta-analysis systematic
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!