研究基于自然语言处理 (NLP) 的症状治疗决策支持系统,用于药物指导
1Trade union, Guilin Medical University, Guilin, China.
Studies in health technology and informatics
|November 26, 2023
概括
自然语言处理 (NLP) 和文本分析在传染病爆发期间识别出发烧和喉疼痛等关键症状. 这项技术有助于选择适当的症状治疗和药物.
科学领域:
- 计算语言学计算语言学
- 医疗信息学医学信息学
- 公共卫生 公共卫生
背景情况:
- 大规模的传染病爆发对医疗保健工作者和患者在症状分析和治疗方面带来了挑战.
- 在疫情爆发的早期阶段,现有系统可能会在快速数据收集和分析方面遇到困难.
研究的目的:
- 评估自然语言处理 (NLP) 和文本分析技术,用于症状分析和症状治疗支持.
- 开发一个预试验的在线系统来选择症状治疗和药物.
主要方法:
- 使用NLP关键词提取和对受感染人口的问卷数据进行文本分析.
- 分析了症状描述和症状治疗药物的疗效.
- 开发了一个在线症状治疗支持药物选择系统.
主要成果:
- 发现的高频症状包括鼻塞,喉痛和发烧.
- 分析表明,治疗方法集中在感冒药,抗炎药和传统中医药中.
- 由于数据不足,在疫情爆发的早期阶段,快速系统具有挑战性.
结论:
- 在爆发期间,NLP和文本分析是识别流行症状的有效工具.
- 一个全面的症状治疗支持系统需要积累的数据样本以获得最佳的性能.
- 该研究产生了在线症状治疗指导的基础系统.
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