New Study Uses Machine Learning To Unveil Non-invasive Biomarkers For Clinical Depression

Researchers from Skoltech, the University of Sharjah, and Al-Farabi Kazakh National University have discovered biological markers for clinical depression that will make diagnostic criteria more objective. Their study uses multimodal data, including MRI examination, electroencephalography, blood tests, genotyping and transcriptome analysis, to create machine-learning models that can reveal integrative biomarkers. This study focuses on transcriptome analysis, which is the study of the complete set of RNA molecules in a cell. The results of this study could lead to more objective diagnostic criteria for clinical depression.