Functional brain-imaging methods provide rich datasets that can be exploited by machine-learning techniques to help assess psychiatric disorders. A recent study uses this approach to identify patients with suicidal thoughts, and to distinguish those who have attempted suicide from those who have not.
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References
Stephan, K. E. et al. Lancet Psychiatry 3, 77–83 (2016).
Just, M. A. et al. Nat. Hum. Behav. 1, https://doi.org/10.1038/s41562-017-0234-y (2017).
Curtis, V. A. et al. Schizophr. Res. 37, 35–44 (1999).
Prvulovic, D., Bokde, A., Fatraco, F. & Hampel, H. Prog. Neurobiol. 95, 557–569 (2011).
Koshino, H. et al. Cereb. Cortex 18, 289–300 (2008).
Harrison, B. J. et al. Arch. Gen. Psychiatry 66, 1189–1200 (2009).
Kassam, K. S., Markey, A. R., Cherkassky, V. L., Loewenstein, G. & Just, M. A. PLoS ONE 8, e66032 (2013).
Horwitz, B. & Rowe, J. B. Prog. Neurobiol. 95, 505–509 (2011).
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Horwitz, B. Identifying suicidal young adults. Nat Hum Behav 1, 860–861 (2017). https://doi.org/10.1038/s41562-017-0239-6
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DOI: https://doi.org/10.1038/s41562-017-0239-6
