Tan Laren D, Nguyen Nolan, Lopez Enrique, Peverini Daniel, Shedd Mathew, Alismail Abdullah, Nguyen H Bryant
Department of Medicine, Loma Linda University Health, Loma Linda, CA, USA.
Department of Cardiopulmonary Sciences, Loma Linda University Health, Loma Linda, CA, USA.
J Asthma Allergy. 2025 Aug 16;18:1179-1191. doi: 10.2147/JAA.S535264. eCollection 2025.
Asthma, a chronic respiratory condition, impacts over 339 million individuals globally, including 25 million in the United States, contributing to significant morbidity and healthcare costs. Despite advances, challenges persist in managing exacerbations, ensuring medication adherence, and patient education. This narrative review explores the transformative potential of artificial intelligence (AI) in improving asthma management through predictive analytics, personalized treatment, and continuous patient engagement. A search of the United States National Library of Medicine's PubMed database was performed for articles pertaining to asthma and artificial intelligence, machine learning (ML), neural network, or deep learning. The current research on AI applications in asthma care was then reviewed, including algorithms, AI-driven tools for personalized medicine, and digital platforms for patient engagement. Case studies and clinical trials assessing AI's impact on predictive accuracy and treatment adherence were reviewed. AI, particularly ML, enhances asthma management by analyzing data from wearables and patient records to predict exacerbations, stratify risk, and inform personalized treatment. Studies demonstrate AI's capability to recommend tailored interventions, monitor adherence through smart applications, and facilitate real-time treatment adjustments. Ethical challenges include ensuring patient trust, data security, and equitable technology access. In conclusion, AI's integration in asthma care holds significant promise for predictive interventions, personalized regimens, and continuous support, ultimately aiming to improve patient outcomes and reduce healthcare burdens. Continued advancements in AI will bridge current care gaps, fostering a patient-centric, proactive approach in asthma management.
哮喘是一种慢性呼吸道疾病，全球有超过3.39亿人受其影响，其中美国有2500万人患病，导致了严重的发病率和医疗成本。尽管取得了进展，但在管理病情加重、确保药物依从性和患者教育方面仍存在挑战。这篇叙述性综述探讨了人工智能（AI）通过预测分析、个性化治疗和持续患者参与来改善哮喘管理的变革潜力。对美国国立医学图书馆的PubMed数据库进行了搜索，以查找与哮喘和人工智能、机器学习（ML）、神经网络或深度学习相关的文章。然后对当前关于人工智能在哮喘护理中的应用研究进行了综述，包括算法、用于个性化医疗的人工智能驱动工具以及用于患者参与的数字平台。对评估人工智能对预测准确性和治疗依从性影响的案例研究和临床试验进行了综述。人工智能，尤其是机器学习，通过分析可穿戴设备和患者记录中的数据来预测病情加重、分层风险并为个性化治疗提供信息，从而增强哮喘管理。研究表明，人工智能有能力推荐量身定制的干预措施，通过智能应用程序监测依从性，并促进实时治疗调整。伦理挑战包括确保患者信任、数据安全和公平的技术获取。总之，人工智能融入哮喘护理对于预测性干预、个性化治疗方案和持续支持具有重大前景，最终目标是改善患者预后并减轻医疗负担。人工智能的持续进步将弥合当前的护理差距，在哮喘管理中形成以患者为中心的积极主动方法。
