一个全面的自然语言处理管道,用于慢性狼疾病
Livia Lilli1,2, Silvia Laura Bosello1, Laura Antenucci1,2
1Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
Studies in health technology and informatics
|August 23, 2024
概括
本研究介绍了一种自然语言处理 (NLP) 方法,用于从电子健康记录 (EHR) 中提取关键患者信息,用于慢性狼病的管理. 这种方法显著提高了数据提取的准确性,有助于临床决策.
科学领域:
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
- 医疗保健中的人工智能
背景情况:
- 电子健康记录 (EHR) 包含大量非结构化的患者数据,对临床决策构成挑战.
- 从电子健康记录中提取特定的临床信息,如疗法,诊断和症状,对于管理慢性疾病如狼至关重要.
研究的目的:
- 开发和评估一种自然语言处理 (NLP) 管道,用于自动提取狼患者的门诊EHR中的疗法,诊断和症状.
- 通过整合基于规则的系统,文本细分,基于变压器的主题分析和临床本体学来增强文本预处理和自动化规则识别.
主要方法:
- 开发了一个全面的NLP管道,结合了基于规则的系统,文本细分,基于变压器的主题分析和临床本体学.
- 该方法应用于来自56名慢性狼病患者的750个意大利语电子健康记录的数据集.
主要成果:
- 该NLP管道实现了高性能,在三个提取的领域 (治疗,诊断,症状) 中,准确性和F-score分别超过97%和90%.
- 综合方法证明了文字预处理和自动规则识别的有效增强.
结论:
- 开发的NLP方法显著自动化了从慢性狼疾病的电子健康记录中提取信息.
- 这种方法有可能集成到EHR系统中,以最大限度地减少人类干预,并支持个性化的数字健康解决方案.
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