Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression.
J Affect Disord April 1, 2018 Facundo Carrillo, Mariano Sigman, Diego Fernández Slezak et al. 57 citations
An algorithm analyzing natural speech from baseline interviews can predict which patients with treatment-resistant depression will respond to psilocybin therapy. The approach uses vocal patterns and linguistic features to forecast treatment outcomes, suggesting that speech biomarkers may enable personalized medicine in mental health. This predictive capability could help identify likely responders before treatment begins, advancing precision psychiatry for depression.