Complex psychiatric disorders pose significant challenges in diagnosis and treatment due to their multifactorial nature and inherent heterogeneity. However, the emergence of Artificial Intelligence (AI)-associated computational tools offers new possibilities for advancing our understanding of these disorders and improving patient care. This article explores the potential of AI-based computational tools in detecting and enhancing the treatment of complex psychiatric disorders, with a specific focus on Major Depressive Disorder. By leveraging integrative analysis techniques, such as bioinformatics and machine learning, on transcriptomics data, promising MDD-related biomarkers and pathways have been identified, paving the way for personalized medicine and targeted interventions.
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Journal of Genetics and Genomes received 65 citations as per Google Scholar report
