自然语言处理和精神分裂症:使用和挑战的范围审查
Antoine Deneault1, Alexandre Dumais2, Marie Désilets2
1Department of Psychiatry and Addictology, Faculty of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada.
Journal of personalized medicine
|July 27, 2024
概括
自然语言处理 (NLP) 为精神分裂症研究提供了潜力,有助于早期诊断和治疗. 本次审查确定了六个关键的NLP应用,强调需要在临床环境中进一步验证.
科学领域:
- 计算语言学计算语言学
- 精神病学是一个精神病学.
- 人工智能的人工智能是人工智能.
背景情况:
- 精神分裂症影响全球人口的1%,其特点是认知,积极和消极的症状.
- 神经递质,特别是多巴胺的不平衡以及遗传/环境因素导致精神分裂症.
- 患者经常表现出明显的语言障碍,包括言语输出和流性减少.
研究的目的:
- 探索自然语言处理 (NLP) 在精神分裂症研究中的多样化应用.
- 综合目前关于NLP技术用于精神分裂症诊断和治疗的研究.
主要方法:
- 使用主要的电子数据库 (Medline,PubMed,Embase,PsycInfo) 进行了全面的范围审查.
- 搜索术语结合了"精神分裂症"和"自然语言处理";数据提取侧重于研究特征,NLP使用,结果和局限性.
- 研究质量被系统地评估.
主要成果:
- 从516篇最初的文章中选择了18项研究,揭示了6个主要的NLP应用.
- 主要应用包括诊断/预测建模,语言现象分析,语音/沟通分析,社交媒体内容分析,临床/认知评估和语言特征分析.
结论:
- 自然语言处理在精神分裂症研究的各个方面都具有显著的实用性.
- 进一步的研究对于验证NLP工具在精神分裂症诊断和治疗干预方面的有效性至关重要.
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