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利用电子病历中的自然语言处理技术确定哮喘预后。

Ascertainment of asthma prognosis using natural language processing from electronic medical records.

机构信息

Department of Health Science Research, Mayo Clinic, Rochester, Minn.

Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minn; Asthma Epidemiology Research Unit, Mayo Clinic, Rochester, Minn.

出版信息

J Allergy Clin Immunol. 2018 Jun;141(6):2292-2294.e3. doi: 10.1016/j.jaci.2017.12.1003. Epub 2018 Feb 10.

DOI:10.1016/j.jaci.2017.12.1003
PMID:29438770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5994178/
Abstract

NLP algorithm successfully determined asthma prognosis (i.e., no remission, long-term remission, and intermittent remission) by taking into account asthma symptoms documented in EMR, and addressed the limitations of billing code- based asthma outcome assessment.

摘要

NLP 算法通过考虑电子病历中记录的哮喘症状，成功地确定了哮喘预后（即无缓解、长期缓解和间歇性缓解），并解决了基于计费代码的哮喘结局评估的局限性。

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Allergy Asthma Proc. 2017 Mar 1;38(2):152-156. doi: 10.2500/aap.2017.38.4021.
3
Predicting asthma outcomes.预测哮喘结局。
预测儿童哮喘预后的人工智能模型。
J Allergy Clin Immunol Glob. 2025 Jan 31;4(2):100429. doi: 10.1016/j.jacig.2025.100429. eCollection 2025 May.
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BMJ Open. 2022 Mar 10;12(3):e051926. doi: 10.1136/bmjopen-2021-051926.
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