Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-24T04:22:41.287Z Has data issue: false hasContentIssue false

Comment on Starke et al.: “Computing schizophrenia: ethical challenges for machine learning in psychiatry”: From machine learning to student learning: pedagogical challenges for psychiatry – Corrigendum

Published online by Cambridge University Press:  04 March 2021

Christophe Gauld
Affiliation:
Department of Psychiatry, University of Grenoble, Avenue du Maquis du Grésivaudan, 38 000 Grenoble, France UMR CNRS 8590 IHPST, Sorbonne University, Paris 1, France
Jean-Arthur Micoulaud-Franchi
Affiliation:
University Sleep Clinic, Services of functional exploration of the nervous system, University Hospital of Bordeaux, Place Amélie Raba-Leon, 33 076 Bordeaux, France USR CNRS 3413 SANPSY, University Hospital Pellegrin, University of Bordeaux, Bordeaux, France
Guillaume Dumas
Affiliation:
Precision Psychiatry and Social Physiology Laboratory, CHU Sainte-Justine Research Center, Department of Psychiatry, University of Montreal, Quebec, Canada Human Brain and Behavior Laboratory, Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, Florida, USA
Rights & Permissions [Opens in a new window]

Abstract

Type
Corrigendum
Copyright
Copyright © The Author(s) 2021. Published by Cambridge University Press

This article was published in Psychological Medicine with some errors in the display of the author's names. This has been corrected online and in the article.

The authors apologise for this error.

References

Gauld, C., Micoulaud-Franchi, J., & Dumas, G. (2020). Comment on Starke et al.: ‘Computing schizophrenia: Ethical challenges for machine learning in psychiatry’: From machine learning to student learning: Pedagogical challenges for psychiatry. Psychological Medicine, 13. doi:10.1017/S0033291720003906CrossRefGoogle Scholar