The wide adoption of electronic health record systems in health care generates big real-world data that open new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in electronic health records. This capability of natural language processing 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 electronic health record data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of natural language processing techniques.

中文翻译：

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人工智能方法使用自然语言处理来推进基于 EHR 的临床研究。


电子健康记录系统在医疗保健领域的广泛采用产生了大量的真实数据，为临床研究开辟了新的场所。由于大量有价值的临床信息被锁定在临床叙述中，自然语言处理技术作为一种人工智能方法已被用来从电子健康记录中的临床叙述中提取信息。这种自然语言处理能力有可能实现自动图表审查，以识别临床护理中具有独特临床特征的患者，并减少定义表型时的方法异质性，从而掩盖过敏、哮喘和免疫学研究中的生物异质性。这篇简短的综述讨论了有关电子健康记录数据二次用于过敏、哮喘和免疫学临床研究的现有文献，并强调了自然语言处理技术的潜力、挑战和影响。