使用自然语言处理来分析非结构化的患者报告结果,来自癌症群体电子健康记录的数据:系统性审查
Jin-Ah Sim1,2, Xiaolei Huang3, Madeline R Horan1
1Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA.
Expert review of pharmacoeconomics & outcomes research
|February 21, 2024
概括
自然语言处理 (NLP) 和机器学习 (ML) 可以从临床笔记中分析患者报告的结果 (PRO). 本综述探讨了在电子健康记录 (EHR) 中对癌症患者数据的NLP/ML应用.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
背景情况:
- 电子健康记录 (EHR) 包含非结构化的患者报告结果 (PRO),提供有价值的临床见解.
- 分析自由文本PROs (症状,生活质量) 对于癌症患者的护理至关重要,但仍未得到充分研究.
- 对癌症群体中非结构化PRO的自然语言处理 (NLP) 和机器学习 (ML) 缺乏全面的审查.
结论:
- 与ML相结合的NLP提供了一种强大的方法,可以利用癌症患者在EHR中的非结构化PRO数据.
- 本系统性审查突出了NLP在分析癌症患者报告结果中的潜在和当前应用.
- 进一步研究和实施NLP技术可以提高临床决策和瘤学患者护理.
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