Objective:

To conduct a comprehensive bibliometric and visualized analysis of the use of artificial intelligence and digital technologies in bipolar disorder from 2000 to 2025, mapping global research trends, collaborations, and technological advances.

Key Findings:

• Digital health technologies are emerging as effective tools for monitoring and managing bipolar disorder, with evidence from recent studies.
• AI applications in bipolar disorder are growing, particularly in mood detection and treatment optimization, as shown in various research.
• Gaps exist in user adherence, privacy concerns, and integration of AI with clinical practices, which need to be addressed for effective implementation.

Interpretation:

The study highlights the potential of AI and digital psychiatry in improving bipolar disorder management while identifying significant barriers to implementation, such as user adherence and privacy issues, and the need for further research.

Limitations:

• Limited integration of AI with clinical endophenotypes, as noted in recent literature.
• Concerns regarding ethical considerations and data security, which are critical in the context of mental health.
• Need for tailored solutions across different illness stages, emphasizing the diversity of bipolar disorder presentations.

Conclusion:

The bibliometric analysis provides actionable insights for clinicians, researchers, and technology developers, emphasizing the importance of addressing existing gaps in research and implementation to enhance bipolar disorder management.