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使用人工智能检测家庭暴力风险:系统审查和元分析协议

Kathleen de Boer¹, Jessica L Mackelprang¹, Maja Nedeljkovic¹

¹Department of Psychological Sciences, Swinburne University of Technology, Hawthorn, Australia.

JMIR research protocols

|December 2, 2024

概括

本系统性审查评估了人工智能 (AI) 使用语音或文本数据识别家庭暴力风险的准确性. 调查结果将指导人工智能开发用于暴力预防策略.

科学领域:

计算社会科学计算社会科学
公共卫生信息学公共卫生信息学
在行为科学中的人工智能

背景情况:

尽管有现有的预防策略,但家庭暴力仍然是一个全球性问题.
需要创新的方法,人工智能 (AI) 是有前途的.
人工智能利用语音或文本数据来检测家庭暴力风险是一个不断增长的研究领域.

研究的目的:

系统地审查和分析人工智能模型的准确性.
区分那些面临家庭暴力行为风险的人与那些没有风险的人.
用文本或语音信号数据进行风险评估.

主要方法:

进行全面的数据库搜索 (IEEE Xplore,PubMed,PsycINFO,EBSCOhost等等) 和灰色文学.
包括使用机器学习进行家庭暴力风险评估的人类成年人的研究 (语音或文本数据).
数据选,全文审查,质量评估 (偏差风险),叙事综合和随机效应元分析 (曲线下的区域).

主要成果:

文献搜索尚未开始 (2024年10月).
该审查将综合当前关于人工智能在检测家庭暴力风险方面的准确性研究.
结果将通过叙事综合,表格和森林地块来呈现.

结论:

这项研究将澄清机器学习模型在识别家庭暴力高风险个人的准确性.
调查结果将为人工智能和机器学习工具的开发提供信息,以预防暴力.
这项研究旨在提高人工智能在缓解家庭暴力方面的有效性.

关键词:

人工智能的人工智能是人工智能.行为行为行为行为.检测检测检测检测检测家庭暴力家庭暴力家庭暴力机器学习是机器学习.心理健康心理健康自然语言处理自然语言处理.政策政策政策政策患病率的流行情况.预防预防预防心理上的痛苦心理上的痛苦公共卫生公共卫生.研究文献研究文献社会政策社会政策社会政策自杀的风险自杀的风险语音信号的特征语音信号的特征

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