Using machine learning to predict outcomes in psychosis

Affiliations

¹ Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK.
² Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK; Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK. Electronic address: matthew.kempton@kcl.ac.uk.
³ Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK; National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK.

Comment

Jonathan Young et al. Lancet Psychiatry. 2016 Oct.

. 2016 Oct;3(10):908-909.

doi: 10.1016/S2215-0366(16)30218-8. Epub 2016 Aug 25.

¹ Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK.
² Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK; Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK. Electronic address: matthew.kempton@kcl.ac.uk.
³ Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 8AF, UK; National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK.

No abstract available

Comment on

Multisite prediction of 4-week and 52-week treatment outcomes in patients with first-episode psychosis: a machine learning approach.
Koutsouleris N, Kahn RS, Chekroud AM, Leucht S, Falkai P, Wobrock T, Derks EM, Fleischhacker WW, Hasan A. Koutsouleris N, et al. Lancet Psychiatry. 2016 Oct;3(10):935-946. doi: 10.1016/S2215-0366(16)30171-7. Epub 2016 Aug 25. Lancet Psychiatry. 2016. PMID: 27569526 Clinical Trial.