Russian AI Detects Depression with 86% Accuracy Using Brain Scans

Russian researchers have created an AI system that detects depression with 86% accuracy. The technology analyses brain scans to distinguish between depressed patients and healthy individuals. This breakthrough could lead to faster diagnoses and more targeted treatments. The team trained the AI using functional MRI data from 70 depressed patients and 70 healthy volunteers. Unlike traditional methods, which rely on five key neural markers, the system identified 20 distinct brain connections linked to depression. It achieved its high accuracy by comparing group differences rather than focusing on individual variations.

Two algorithms worked together to map brain network organisation. One detected disruptions in neuron signalling, while the other assessed oxidative stress and cell damage—both hallmarks of major depressive disorder. The results far exceeded standard clinical assessments, which typically reach only 50% accuracy. Funded by the Russian Science Foundation, the study was published in *Chaos, Solitons and Fractals*. The researchers now plan to adapt the algorithm for other conditions, including schizophrenia and bipolar disorder.

The AI’s ability to pinpoint depression-related brain patterns could transform mental health diagnostics. Clinicians may soon rely on objective neuroimaging data rather than subjective evaluations. Further testing will determine how widely the system can be applied in medical settings.