Artificial intelligence (AI) has been successfully exploited in diagnosing many mental disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI models in diagnosing different mental disorders. This umbrella review aims to synthesize results of previous systematic reviews on the performance of AI models in diagnosing mental disorders. To identify relevant systematic reviews, we searched 11 electronic databases, checked the reference list of the included reviews, and checked the reviews that cited the included reviews. Two reviewers independently selected the relevant reviews, extracted the data from them, and appraised their quality. We synthesized the extracted data using the narrative approach. We included 15 systematic reviews of 852 citations identified. The included reviews assessed the performance of AI models in diagnosing Alzheimer’s disease (n = 7), mild cognitive impairment (n = 6), schizophrenia (n = 3), bipolar disease (n = 2), autism spectrum disorder (n = 1), obsessive-compulsive disorder (n = 1), post-traumatic stress disorder (n = 1), and psychotic disorders (n = 1). The performance of the AI models in diagnosing these mental disorders ranged between 21% and 100%. AI technologies offer great promise in diagnosing mental health disorders. The reported performance metrics paint a vivid picture of a bright future for AI in this field. Healthcare professionals in the field should cautiously and consciously begin to explore the opportunities of AI-based tools for their daily routine. It would also be encouraging to see a greater number of meta-analyses and further systematic reviews on performance of AI models in diagnosing other common mental disorders such as depression and anxiety.

人工智能 (AI) 已成功用于诊断许多精神障碍。许多系统评价总结了人工智能模型在诊断不同精神障碍方面的准确性的证据。这篇综述旨在综合先前关于人工智能模型在诊断精神障碍方面的表现的系统评价的结果。为了识别相关的系统评价，我们检索了 11 个电子数据库，检查了纳入评论的参考列表，并检查了引用了纳入评论的评论。两名审稿人独立选择相关评论，从中提取数据，并对其质量进行评价。我们使用叙述方法合成提取的数据。我们纳入了 15 篇对 852 篇已确定引文的系统评价。n  = 7)、轻度认知障碍 ( n  = 6)、精神分裂症 ( n  = 3)、双相情感障碍 ( n  = 2)、自闭症谱系障碍 ( n  = 1)、强迫症 ( n  = 1)、创伤性应激障碍 ( n  = 1) 和精神障碍 ( n = 1)。人工智能模型在诊断这些精神障碍方面的表现在 21% 到 100% 之间。人工智能技术在诊断精神健康障碍方面提供了巨大的希望。报告的性能指标生动地描绘了人工智能在该领域的光明未来。该领域的医疗保健专业人员应该谨慎而有意识地开始探索基于人工智能的工具在他们的日常生活中的机会。看到更多关于人工智能模型在诊断其他常见精神障碍（如抑郁症和焦虑症）中的表现的荟萃分析和进一步系统评价也将令人鼓舞。