Will connectome-based predictive modeling change how we care for people at risk of late-life suicide? A novel two-step modeling approach used by Gao et al. in their study sheds light on the road ahead.
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References
Naghavi, M. et al. BMJ 364, l94 (2019).
De Leo, D. Nat. Aging 2, 7–12 (2022).
Kjolseth, I., Ekeberg, O. & Steihaug, S. Int. Psychogeriatr. 21, 903–912 (2009).
Szucs, A. et al. Int. J. Geriatr. Psychiatry 35, 384–395 (2020).
Szanto, K. et al. Eur. Neuropsychopharmacol. 40, 85–98 (2020).
Belsher, B. E. et al. JAMA Psychiatry 76, 642–651 (2019).
Tomasi, D. & Volkow, N. D. Mol. Psychiatry 17, 549–558 (2012).
Gao, M. et al. Nat. Ment. Health. https://doi.org/10.1038/s44220-022-00007-7 (2023).
Shen, X. et al. Nat Protoc 12, 506–518 (2017).
Wang, D. W. L. & Colucci, E. BJPsych Bull. 41, 169–171 (2017).
Varoquaux, G. et al. NeuroImage 145, 166–179 (2017).
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Barredo, J., Namaky, N. Neural predictors of late-life suicide risk. Nat. Mental Health 1, 86–87 (2023). https://doi.org/10.1038/s44220-022-00006-8
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DOI: https://doi.org/10.1038/s44220-022-00006-8
