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Updated: Jul 5, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

通过开放健康自然语言处理联盟 (Open Health Natural Language Processing Consortium) 和进化为下一代临床试验网络 (Evolve to Next-Gen Accrual to

Sunyang Fu¹, Min Ji Kwak², Jaerong Ahn¹

¹McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, United States.

The journals of gerontology. Series A, Biological sciences and medical sciences

|September 29, 2025

概括

自然语言处理 (NLP) 可以识别电子健康记录 (EHR) 中的错觉,但多站点实施面临挑战. 一种协作方法正在开发一种标准化的NLP模型,用于可扩展的,跨机构的妄想检测.

科学领域:

临床信息学临床信息学
自然语言处理自然语言处理.
医疗保健研究医疗保健研究

背景情况:

痴呆症在临床环境中经常被诊断不足,并且没有被计费.
在大型研究中,手动查看图表以识别妄想是不切实际的.
自然语言处理 (NLP) 提供了一个从电子健康记录 (EHR) 中提取临床信息的解决方案.

研究的目的:

为国家一体化标准化和评估基于NLP的妄想检测模型.
解决在各个机构实施NLP的挑战,以便在不同机构中识别错觉.
为了更广泛的可用性,将NLP模型转化为i2b2 / ENACT平台.

主要方法:

在 ENACT NLP 工作组内成立了 Delirium 兴趣小组.
进行了多个站点的上下文调查,以确定实施挑战.
进行了多站点NLP评估,以评估模型性能变化.

主要成果:

确定了关键挑战:查实践的变化,需要协调定义,以及时间逻辑的复杂性.
在NLP模型中观察到性能下降,原因是不同地点的选,文档和笔记结构的差异.
突出了特定地点的变化对模型实施和性能的影响.

结论:

这项工作是迈向可扩展,标准化的NLP基于妄检测的关键第一步.
一种协作方法确定了影响NLP模型性能的共同挑战和特定场所的问题.
开发了一个强大的框架,用于在异构的电子健康记录系统中识别错觉,未来的工作重点是提高有效性和转化影响.

关键词:

人工智能的人工智能狂妄症是什么意思狂妄症是什么意思电子健康记录电子健康记录自然语言处理自然语言处理.翻译人工智能翻译AI

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