中国儿童保健杂志 ›› 2025, Vol. 33 ›› Issue (5): 529-532.DOI: 10.11852/zgetbjzz2024-1284

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人工智能在儿童支气管哮喘诊治与管理中的应用进展

谭红1, 周雪花2, 吴华杰2, 王敏2, 周晗2, 苏慧3, 孙新2   

  1. 1.西安医学院研究生工作部,陕西 西安 710068;
    2.空军军医大学西京医院儿科;
    3.空军军医大学西京医院老年病二科
  • 收稿日期:2024-11-22 修回日期:2025-02-25 发布日期:2025-04-30 出版日期:2025-05-10
  • 通讯作者: 孙新,E-mail: sunxin6@fmmu.edu.cn
  • 作者简介:谭红(1998—),女,硕士在读,主要研究方向为儿童呼吸系统疾病、过敏性疾病。
  • 基金资助:
    陕西省技术创新引导专项(S2022-YD-QFY-0063);西安市科技局医学研究一般项目(24YXYJ0145)

Application of artificial intelligence in the diagnosis and management of bronchial asthma in children

TAN Hong1, ZHOU Xuehua2, WU Huajie2, WANG Min2, ZHOU Han2, SU Hui3, SUN Xin2   

  1. 1. Department of Postgraduate Studies, Xi'an Medical University, Xi'an, Shaanxi 710068,China;
    2. Department of Pediatrics, Xijing Hospital, Air Force Medical University;
    3. Department of Geriatrics, Xijing Hospital, Air Force Medical University
  • Received:2024-11-22 Revised:2025-02-25 Online:2025-05-10 Published:2025-04-30
  • Contact: SUN Xin, E-mail: sunxin6@fmmu.edu.cn

摘要: 人工智能作为一种可以辅助甚至是替代人类某些功能的新型技术,其在疾病诊断、治疗和管理中的应用,对于提高疾病诊断的准确率、实现个体化治疗和管理均有很大作用。支气管哮喘是最常见的气道慢性炎症性疾病之一,其诊断、治疗和管理与监测方面一直备受关注。人工智能可通过表示学习、机器学习、深度学习和自然语言处理等技术收集并分析大量的文字、图像和听觉数据,建立复杂、非线性的关系,以此构建模型,来协助医生对支气管哮喘进行识别、治疗和管理。本文主要从支气管哮喘的诊断分型、治疗和管理与监测角度论述了人工智能在儿童支气管哮喘中的应用及研究进展,并简要分析各种智能辅助方法的优势和局限性。

关键词: 支气管哮喘, 人工智能, 诊断, 管理

Abstract: Artificial intelligence (AI), as an emerging technology capable of augmenting or even replacing certain human functions, has significant potential in enhancing the accuracy of disease diagnosis, enabling personalized treatment, and improving disease management. Bronchial asthma, one of the most prevalent chronic inflammatory airway diseases, has long been a focus in terms of its diagnosis, treatment, and management. AI can utilize techniques such as representation learning, machine learning, deep learning, and natural language processing to collect and analyze vast amounts of textual, visual, and auditory data. By establishing complex, non-linear relationships, AI can construct models to assist physicians in the identification, treatment, and management of bronchial asthma. This paper primarily discusses the application and research progress of AI in pediatric bronchial asthma from the perspectives of diagnostic classification, treatment, and management and monitoring. Additionally, it briefly analyzes the advantages and limitations of various intelligent assistance methods.

Key words: bronchial asthma, artificial intelligence, diagnosis, management

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