应用于焦虑障碍识别的人工智能技术:系统性审查
Edgar Degante-Aguilar1, Roberto Angel Melendez-Armenta1, Giovanni Luna-Chontal1
1Affective Computing and Educational Innovation Laboratory, Division of Graduate Studies and Research, Tecnológico Nacional de México-Instituto Tecnológico Superior de Misantla, Misantla, Veracruz, Mexico.
Frontiers in digital health
|December 10, 2025
概括
人工智能 (AI) 方法在检测焦虑障碍方面比传统测试更准确. 这篇评论分析了AI.
科学领域:
- 心理健康诊断 心理健康诊断
- 医疗保健中的人工智能
- 计算精神病学是一种计算精神病学.
背景情况:
- 焦虑障碍对全球的健康构成重大负担.
- 焦虑障碍的传统诊断方法在准确性和可访问性方面存在局限性.
- 人工智能 (AI) 的整合为改进的诊断工具提供了潜力.
研究的目的:
- 系统地审查和分析目前的人工智能 (AI) 方法来检测焦虑障碍.
- 评估AI驱动的诊断方法的准确性和范围.
- 为研究人员,临床医生和开发人员提供基于AI的心理健康方面的见解.
主要方法:
- 按照PRISMA指南进行的系统审查.
- 在IEEE Xplore,PubMed,ScienceDirect和SpringerLink中进行的搜索.
- 包括专注于定量数据和人工智能技术用于焦虑症诊断的研究.
主要成果:
- 分析了119项关于机器学习和深度学习应用的研究.
- 人工智能方法利用了各种数据来源:自我报告,生理和社交网络数据.
- 与传统方法相比,人工智能驱动的检测显示出更高的准确性.
结论:
- 人工智能在提高焦虑障碍的检测和治疗方面发挥着至关重要的作用.
- 本综述提供了关于人工智能在焦虑诊断方面的进展的全面概述.
- 这些发现指导了未来的研究和将AI整合到精神卫生保健实践中.
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