Review on the use of AI-based methods and tools for treating mental conditions and mental rehabilitation

Vladimir Khorev, Anton Kiselev, Artem Badarin, Vladimir Antipov, Oxana Drapkina, Semen Kurkin, Alexander Hramov
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Abstract

This review provides a thorough examination of recent developments in artificial intelligence analysis methods within mental and psychiatry field. By analyzing and comparing results obtained with various tools and techniques, we provide a comprehensive and systematic understanding of applications. Our main methods include meta-analysis, search queries with the keywords and network-based approach. In our analysis, we observed that terms associated with robotics, human–computer interaction, speech perception, and certain applications, such as chronic fatigue syndrome and psychological adaptation, have been gradually losing prominence. And conversely, techniques such as deep learning, virtual reality, and virtual assistance are gaining traction, and increasing interest was noted for applications involving autistic spectrum disorders, mild cognitive impairments, and psychiatric research areas. The structured and organized presentation of information, along with the accompanying visualizations and diagrams, makes it a valuable resource for scientists and researchers working in the domains of artificial intelligence.

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关于使用基于人工智能的方法和工具治疗精神疾病和精神康复的综述
本综述深入探讨了人工智能分析方法在精神和精神病学领域的最新发展。通过分析和比较使用各种工具和技术获得的结果,我们提供了对应用的全面而系统的理解。我们的主要方法包括元分析、关键词搜索查询和基于网络的方法。在分析过程中,我们发现与机器人、人机交互、语音感知和某些应用(如慢性疲劳综合症和心理适应)相关的术语逐渐失去了突出地位。反之,深度学习、虚拟现实和虚拟辅助等技术正受到越来越多的关注,涉及自闭症谱系障碍、轻度认知障碍和精神病学研究领域的应用也受到越来越多的关注。该书结构严谨、条理清晰地介绍了相关信息,并附有可视化图表,是人工智能领域科学家和研究人员的宝贵资料。
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