Georgakopoulou Vasiliki E
Department of Pathophysiology/Pulmonology, Laiko General Hospital, Athens, GRC.
Cureus. 2024 Jul 1;16(7):e63635. doi: 10.7759/cureus.63635. eCollection 2024 Jul.
Respiratory tract infections (RTIs) such as pneumonia, bronchitis, and COVID-19 are significant global health concerns due to their high morbidity and mortality rates. The advent of artificial intelligence (AI) offers innovative solutions across various aspects of RTI management, including diagnosis, prediction, treatment, and prevention. AI algorithms enhance diagnostic accuracy by analyzing extensive data from electronic health records and imaging studies, often surpassing human radiologists in identifying diseases such as pneumonia. For instance, AI-based image recognition tools have demonstrated remarkable precision in detecting pneumonia from chest X-rays. Additionally, AI models can predict disease outbreaks and optimize public health responses, as exemplified during the COVID-19 pandemic where AI predicted infection hotspots and evaluated the effectiveness of containment measures. In personalized medicine, AI tailors treatments based on individual patient profiles, thereby improving therapeutic outcomes and accelerating drug discovery. Wearable AI devices facilitate early detection and prevention of RTIs through continuous health monitoring. Despite its transformative potential, AI implementation in healthcare faces challenges, including data privacy, algorithm transparency, and ethical concerns. Addressing these issues necessitates collaboration among technologists, healthcare providers, and policymakers to ensure responsible and equitable integration of AI technologies. This editorial underscores the transformative potential of AI in managing RTIs and calls for robust frameworks to harness AI's benefits while safeguarding patient rights.
诸如肺炎、支气管炎和新冠肺炎等呼吸道感染（RTIs），因其高发病率和死亡率，成为全球重大的健康问题。人工智能（AI）的出现为呼吸道感染管理的各个方面提供了创新解决方案，包括诊断、预测、治疗和预防。人工智能算法通过分析来自电子健康记录和影像学研究的大量数据来提高诊断准确性，在识别肺炎等疾病方面常常超过人类放射科医生。例如，基于人工智能的图像识别工具在从胸部X光片中检测肺炎方面已显示出极高的准确性。此外，人工智能模型可以预测疾病爆发并优化公共卫生应对措施，如在新冠肺炎疫情期间，人工智能预测了感染热点并评估了防控措施的有效性。在个性化医疗中，人工智能根据个体患者的情况定制治疗方案，从而改善治疗效果并加速药物研发。可穿戴人工智能设备通过持续的健康监测，有助于呼吸道感染的早期检测和预防。尽管人工智能具有变革潜力，但在医疗保健领域的应用面临挑战，包括数据隐私、算法透明度和伦理问题。解决这些问题需要技术专家、医疗服务提供者和政策制定者之间的合作，以确保人工智能技术得到负责任且公平的整合。这篇社论强调了人工智能在管理呼吸道感染方面的变革潜力，并呼吁建立强大的框架，以利用人工智能的益处同时保障患者权益。
