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Scientists identify workflow algorithm to predict psychosis

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IMAGE: Artificial intelligence may help predict psychosis in young patients with clinical high-risk syndromes or recent-onset depression.
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Credit: Gerd Altmann
Scientists from the Max Planck Institute of Psychiatry, led by Nikolaos Koutsouleris, combined psychiatric assessments with machine-learning models that analyse clinical and biological data. Although psychiatrists make very accurate predictions about positive disease outcomes, they might underestimate the frequency of adverse cases that lead to relapses. The algorithmic pattern recognition helps physicians to better predict the course of disease.
The results of the study show that it is the combination of artificial and human intelligence that optimizes the prediction of mental illness. This algorithm enables us to improve the prevention of psychosis, especially in young patients at high risk or with emerging depression, and to intervene in a more targeted and well-timed mann ....

Nikolaos Koutsouleris , Dominicb Dwyer , Franziska Degenhardt , Max Planck Institute Of Psychiatry , Max Planck Institute , Machine Learning Workflows , Patients With Clinical High Risk Syndromes , Recent Onset Depression , Medicine Health , Mental Health , Depression Anger , சமீப தொடக்கம் மனச்சோர்வு , மருந்து ஆரோக்கியம் , மன ஆரோக்கியம் , மனச்சோர்வு கோபம் ,