人工智能用于预测抑郁,焦虑和压力使用心理测量数据
Tamer ShamsEldin1, Sarah Gaber2, Shuja Ansari3
1Technical Research Center, Cairo, 11765, Egypt.
Scientific reports
|October 24, 2025
概括
人工智能 (AI) 可以使用心理数据准确预测抑郁症,焦虑和压力. 这种人工智能驱动的心理健康查显示出高准确度,为早期检测铺平了道路.
科学领域:
- 计算精神病学是一种计算精神病学.
- 数字心理健康数字心理健康
背景情况:
- 心理健康至关重要,但由于耻辱和进入障碍,经常被忽视.
- 早期发现抑郁,焦虑和压力等心理状况对于及时干预至关重要.
研究的目的:
- 评估人工智能 (AI) 在预测常见心理状况方面的有效性.
- 用心理测量和人口统计数据评估各种机器学习模型的性能.
主要方法:
- 对39,775名参与者的抑郁焦虑压力表-42 (DASS-42) 问卷答案进行分析.
- 预处理包括处理缺失的数据,标准化和有效性检查.
- 使用交叉验证对五种机器学习模型 (决策树,随机森林,k-NN,天真贝叶斯,SVM) 的评估.
主要成果:
- 支持矢量机 (SVM) 模型表现出卓越的预测准确性.
- 在SVM中,抑郁症的准确率达到99.3%,焦虑症为98.9%,压力为98.8%.
- 人工智能模型在根据问卷数据识别心理状况方面表现出很高的表现.
结论:
- 基于人工智能的方法显示出早期心理健康查的巨大潜力.
- 这项研究强调了机器学习在分析心理测量数据以预测心理状况方面的实用性.
- 进一步的临床验证对于在现实世界医疗保健环境中实施这些AI工具至关重要.
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