S70. INDIVIDUALIZED DIAGNOSIS OF PSYCHOSIS BASED ON MACHINE LEARNING FROM FUNCTIONAL MAGNETIC RESONANCE DATA USING AN EMOTIONAL AUDITORY PARADIGM

摘要

Recently there has been an increasing interest in the use of machine learning techniques to neuroimaging data, in order to discriminate patients with schizophrenia from healthy control. However, until now, these tools have not been useful enough to be integrated into the clinical practice (Arbabshirani MR et al 2016). In the last 10 years we have been using an fMRI auditory emotional paradigm specifically designed for psychosis (Sanjuan et al 2007). This paradigm showed sensitivity to detect changes in brain activation after CBT treatment in patients with persistent auditory hallucinations (Aguilar et al 2018).