Division of Allergy, Asthma, Pulmonary and Sleep Medicine, Children's Mercy Hospital, Kansas City, Missouri, USA.
Curr Opin Allergy Clin Immunol. 2024 Oct 1;24(5):305-312. doi: 10.1097/ACI.0000000000001015. Epub 2024 Jul 24.
Anaphylaxis is a severe, potentially life-threatening allergic reaction that requires rapid identification and intervention. Current management includes early recognition, prompt administration of epinephrine, and immediate medical attention. However, challenges remain in accurate diagnosis, timely treatment, and personalized care. This article reviews the integration of artificial intelligence and machine learning in enhancing anaphylaxis management.
Artificial intelligence and machine learning can analyze vast datasets to identify patterns and predict anaphylactic episodes, improve diagnostic accuracy through image and biomarker analysis, and personalize treatment plans. Artificial intelligence-powered wearable devices and decision support systems can facilitate real-time monitoring and early intervention. The ethical considerations of artificial intelligence use, including data privacy, transparency, and bias mitigation, are also discussed.
Future directions include the development of predictive models, enhanced diagnostic tools, and artificial intelligence-driven educational resources. By leveraging artificial intelligence and machine learning, healthcare providers can improve the management of anaphylaxis, ensuring better patient outcomes and advancing personalized medicine.
过敏反应是一种严重的、潜在危及生命的过敏反应，需要快速识别和干预。目前的治疗包括早期识别、及时给予肾上腺素和立即就医。然而，在准确诊断、及时治疗和个性化护理方面仍存在挑战。本文综述了人工智能和机器学习在增强过敏反应管理中的应用。
人工智能和机器学习可以分析大量数据集以识别模式和预测过敏反应发作，通过图像和生物标志物分析提高诊断准确性，并制定个性化治疗计划。人工智能驱动的可穿戴设备和决策支持系统可以促进实时监测和早期干预。还讨论了人工智能使用的伦理问题，包括数据隐私、透明度和偏差缓解。
未来的方向包括开发预测模型、增强诊断工具和人工智能驱动的教育资源。通过利用人工智能和机器学习，医疗保健提供者可以改善过敏反应的管理，确保更好的患者结局并推进个性化医疗。
