Abstract
Early detection of neuropsychiatric disorders remains a critical challenge in modern medicine due to the complex, multifactorial nature of these conditions and the absence of reliable single-modality diagnostic markers. Disorders such as depression, schizophrenia, and bipolar disorder are characterized by heterogeneous clinical presentations and overlapping biological mechanisms, often leading to delayed diagnosis and suboptimal treatment outcomes. In this context, artificial intelligence (AI) has emerged as a transformative tool capable of integrating diverse data sources and identifying subtle patterns associated with early disease onset.
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