Mapping scientific trends in bipolar disorder and digital psychiatry (2000-2025): A bibliometric and visualized analysis of AI-driven diagnosis and digital interventions

This study aims to map and visualize global research trends related to bipolar disorder (BD), with a focus on artificial intelligence (AI)-driven diagnosis and digital psychiatry from 2000 to 2025.

A bibliometric analysis was conducted using publications retrieved from Web of Science, Scopus, and PubMed, covering the period from January 1, 2000, to June 30, 2025. All data were extracted from databases at the time of search in mid-2025, and no future or projected data were included. After deduplication and data cleaning, 4,753 relevant articles were included. VOSviewer was utilized to perform co-authorship, keyword co-occurrence, and bibliographic coupling network analysis. Descriptive statistics, including annual publication trends, authorship patterns, and institutional contributions, were analyzed using Excel Pivot Tables.

Scientific output in this field has grown significantly since 2015, with the United States (n=1850), United Kingdom (n=750), and China (n=620) leading in publications. Harvard University emerged as the most prolific institution. Author collaboration networks identified Eduard Vieta and Lars Vedel Kessing as key contributors. Keyword analysis revealed four dominant clusters: AI/machine learning, clinical diagnosis and biomarkers, cognitive function and quality of life, and digital interventions via smartphones and wearables. Journals such as Journal of Affective Disorders and JMIR Mental Health are central to recent literature. However, global collaboration remains limited, and the integration of digital phenotyping with biological data is still in early stages.

Research in BD is shifting toward AI-enabled and digital mental health approaches. Future studies should enhance interdisciplinary collaboration, focus on multimodal data integration, and promote equitable global access to digital psychiatric tools.