# Researchers create machine learning-based classifier that could aid early diagnosis of psychosis
The onset of psychosis can be predicted before it occurs, using a machine-learning tool which can classify MRI brain scans into those who are healthy and those at risk of a psychotic episode.
An international consortium including researchers from the University of Tokyo, used the classifier to compare scans from over 2,000 people from 21 global locations. About half of the participants had been identified as being clinically at high risk of developing psychosis.
Using training data, the classifier was 85% accurate at differentiating between people who were not at risk and those who later experienced overt psychotic symptoms. Using new data, it was 73% accurate. The work has been published in Molecular Psychiatry.
Scientific paper:
Using Brain Structural Neuroimaging Measures to Predict Psychosis Onset for Individuals at Clinical High-Risk. Molecular Psychiatry (2024). DOI: 10.1038/s41380-024-02426-7