Publication:

Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth

Loading...
Thumbnail Image

Date

2017

Journal Title

Journal ISSN

Volume Title

Publisher

Springer Nature
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Just, Marcel Adam, Lisa Pan, Vladimir L. Cherkassky, Dana L. McMakin, Christine Cha, Matthew K. Nock, and David Brent. 2017. “Machine Learning of Neural Representations of Suicide and Emotion Concepts Identifies Suicidal Youth.” Nature Human Behaviour (October 30). doi:10.1038/s41562-017-0234-y. THIS ARTICLE WAS RETRACTED ON 06 APRIL 2023.

Abstract

Retraction to: Nature Human Behaviour https://doi.org/10.1038/s41562-017-0234-y published online 30 October 2017

The authors are retracting this article after concerns were raised about the validity of their machine learning method in a Matters Arising1. While revising their response to these concerns, the authors confirmed that their method was indeed flawed, which affects the conclusions of the article. Specifically, the stepwise classification method used in the article overestimated the classification accuracy of who is a suicidal ideator because the features of the classifier were tuned to that particular dataset. The authors aim to demonstrate the predictive value of machine learning applied to fMRI data for the classification of suicidal ideators using new data and analyses in an independent future publication. All authors agree to this retraction.

Description

Other Available Sources

Research Data

Keywords

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Related Stories