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Towards increasing the clinical applicability of machine learning biomarkers in psychiatry

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Matters Arising to this article was published on 05 April 2021

The Original Article was published on 30 October 2017

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Fig. 1: Effects of parameter choices on the accuracy for differentiation between suicide ideators and controls.

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Authors and Affiliations

  1. Institute of Neuroscience and Medicine: Brain and Behaviour (INM-7), Jülich Research Centre, Jülich, Germany

    Juergen Dukart, Susanne Weis, Sarah Genon & Simon B. Eickhoff

  2. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Juergen Dukart, Susanne Weis, Sarah Genon & Simon B. Eickhoff

Authors
  1. Juergen Dukart
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  2. Susanne Weis
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  3. Sarah Genon
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  4. Simon B. Eickhoff
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Contributions

J.D. and S.B.E. designed the work and wrote the manuscript. S.G. and S.W. contributed to interpretation and substantively revised the manuscript.

Corresponding author

Correspondence to Simon B. Eickhoff.

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The authors declare no competing interests.

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Peer review information Nature Human Behaviour thanks the anonymous reviewers for their contribution to the peer review of this work.

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Dukart, J., Weis, S., Genon, S. et al. Towards increasing the clinical applicability of machine learning biomarkers in psychiatry. Nat Hum Behav 5, 431–432 (2021). https://doi.org/10.1038/s41562-021-01085-w

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