自然语言处理可促进基于EHR的过敏，哮喘和免疫学临床研究
2020/01/07
摘要
电子医疗记录系统（EHR）在医疗保健中的广泛采用产生了大量的真实世界数据，为开展临床研究提供了新的场所。 由于大量有价值的临床信息被锁定在临床叙述中，自然语言处理（NLP）技术作为一种人工智能方法已被用来从EHR的临床叙述中提取信息。 NLP的这一能力有可能实现自动图表审查，以识别在临床护理中具有独特临床特征的患者，并减少在定义表型方面的方法学异质性，从而模糊过敏、哮喘和免疫学研究中的生物异质性。这篇简短综述讨论了有关EHR数据在过敏，哮喘和免疫学临床研究中的二次使用的最新文献，并重点介绍了NLP技术的潜力，挑战和意义。
Juhn Y, Liu H.
Abstract
The wide adoption of electronic health record systems (EHRs) in health care generates big real-world data that opens new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing (NLP) techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in EHRs. This capability of NLP potentially enables automated chart review for identifying patients with distinctive clinical characteristics in clinical care and reduces methodological heterogeneity in defining phenotype obscuring biological heterogeneity in research concerning allergy, asthma, and immunology. This brief review discusses the current literature on the secondary use of EHR data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of NLP techniques.
电子医疗记录系统（EHR）在医疗保健中的广泛采用产生了大量的真实世界数据，为开展临床研究提供了新的场所。 由于大量有价值的临床信息被锁定在临床叙述中，自然语言处理（NLP）技术作为一种人工智能方法已被用来从EHR的临床叙述中提取信息。 NLP的这一能力有可能实现自动图表审查，以识别在临床护理中具有独特临床特征的患者，并减少在定义表型方面的方法学异质性，从而模糊过敏、哮喘和免疫学研究中的生物异质性。这篇简短综述讨论了有关EHR数据在过敏，哮喘和免疫学临床研究中的二次使用的最新文献，并重点介绍了NLP技术的潜力，挑战和意义。
(中日友好医院呼吸与危重症医学科 王瑞茵 摘译 林江涛 审校)
(J Allergy Clin Immunol. 2019 Dec 26. pii: S0091-6749(19)32604-1. doi: 10.1016/j.jaci.2019.12.897. [Epub ahead of print])
Natural language processing to advance EHR-based clinical research in Allergy, Asthma, and Immunology. (J Allergy Clin Immunol. 2019 Dec 26. pii: S0091-6749(19)32604-1. doi: 10.1016/j.jaci.2019.12.897. [Epub ahead of print])
Juhn Y, Liu H.
Abstract
The wide adoption of electronic health record systems (EHRs) in health care generates big real-world data that opens new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing (NLP) techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in EHRs. This capability of NLP potentially enables automated chart review for identifying patients with distinctive clinical characteristics in clinical care and reduces methodological heterogeneity in defining phenotype obscuring biological heterogeneity in research concerning allergy, asthma, and immunology. This brief review discusses the current literature on the secondary use of EHR data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of NLP techniques.
上一篇：
成纤维细胞形成的纤维胶原组织缺陷导致哮喘患者气道重塑
下一篇：
鼻病毒激发后生物标记物波动动态显示哮喘患者适应能力丧失
