人工智能在抑郁症检测和诊断中的应用:对趋势的图书识别和视觉分析以及未来的方向
Wenbo Ren1, Xiali Xue2, Lu Liu3
1Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
JMIR mental health
|September 29, 2025
概括
人工智能 (AI) 正在彻底改变抑郁症诊断,朝着客观,数据驱动的方法迈进. 这项研究分析了AI.
科学领域:
- 人工智能 (AI) 在抑郁症检测和诊断中的应用的图书统计和视觉分析.
- 在人工智能辅助的心理健康诊断中绘制全球研究趋势,智力结构和新兴前沿.
背景情况:
- 抑郁症诊断依赖于主观评估,这对准确性和一致性构成了挑战.
- 人工智能 (AI) 提供了更客观,更有效的抑郁症检测方法的潜力.
- 了解AI在抑郁症诊断中的演变作用对于未来的研究和临床应用至关重要.
研究的目的:
- 进行对全球研究AI用于抑郁症检测和诊断 (2015-2024) 的综合文献计量和视觉分析.
- 确定这个跨学科领域的研究趋势,知识基础和新兴前沿.
主要方法:
- 在科学网络核心集合 (2015-2024) 中系统的文献搜索.
- 使用CiteSpace的图书识别软件分析了2304篇被检索的文章.
- 检查时间趋势,关键词动态,协作和共同引用网络.
主要成果:
- 出版物和引文的指数式增长,特别是在2018年后,表明兴趣的增加.
- 从传统的机器学习转向深度学习,多模式融合和客观生物标志物 (EEG,面部表情).
- 来自中国和美国的领先贡献,与日益增长的国际合作;计算机科学,神经科学和精神病学的跨学科基础.
结论:
- 人工智能在抑郁症诊断中的整合正在成熟,强调客观,数据驱动的临床相关性方法.
- 需要加强跨学科/国际合作,伦理框架,以及对人工智能创新的公平翻译.
- 研究结果为研究人员,临床医生和决策者提供了洞察力,以在全球范围内推进人工智能辅助抑郁症诊断.
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