识别具有自然语言处理的手术候选人:系统性审查
Sheryn Tan1, Charis Tang1, Jeng Swen Ng1
1University of Adelaide, Adelaide, SA 5005, Australia.
概括
自然语言处理 (NLP) 在识别符合手术评估条件的患者方面表现有前途,可能是在临床转诊前几年. 需要进一步的研究来探索各种数据集和实施影响.
科学领域:
- 神经学 神经学
- 医疗信息学 医疗信息学
背景情况:
- 手术是对抗药性的未充分使用的治疗方法.
- 自然语言处理 (NLP) 可能有助于确定适合手术评估的候选人.
- 为此目的使用NLP的可行性需要进一步调查.
研究的目的:
- 系统地审查关于NLP在确定适合手术评估的患者中使用NLP的文献.
- 在这种情况下,评估NLP算法的性能和潜力.
主要方法:
- 按照PRISMA指南进行了系统审查.
- 搜索的数据库包括PubMed,EMBASE和科克兰图书馆.
- 该审查在PROSPERO.上进行了前性注册.
主要成果:
- 六项研究符合纳入标准,主要使用支持向量机器.
- 所有研究都在识别潜在手术候选人方面表现中等至高.
- 已经证明NLP在临床转诊前1-2年识别患者,但缺乏实施影响研究.
结论:
- NLP为确定适合手术评估的患者提供了一种有前途的方法.
- 建议使用各种数据集和分析方法进行进一步的研究.
- 评估实施NLP算法的现实影响的研究是有益的.
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