急性呼吸窘迫综合征（ARDS）特征为肺泡毛细血管通透性增加和低氧血症，常导致多器官功能衰竭。早期识别与干预，特别是机械通气的优化、容量管理、抗炎治疗等，以及一些新型治疗方法，如俯卧位通气和体外膜肺氧合（ECMO）能显著提升患者生存率，缩短ICU住院时间，降低医疗费用。为优化ARDS诊治，需整合研究成果、临床指南和实践经验，构建系统的知识体系。GPT作为智能工具，在医学领域展现出巨大潜力。它能高效检索医学数据库，建立知识图谱，开发在线平台，提供个性化推荐，帮助医生快速掌握最新进展。同时，GPT还能生成高质量的教育培训资料，满足不同医务人员的培训需求。在线培训中，GPT结合模拟病例和VR/AR技术，创造沉浸式学习环境，提升基层医生的诊疗能力。GPT还能赋能远程诊疗，特别是在资源匮乏地区，通过远程诊断和辅助，加速治疗进程。在临床决策支持方面，GPT能分析电子病历，提供早期预警和干预建议，定制个性化治疗计划。它还促进多学科协作和技术交流。在资源配置上，GPT能分析数据，为政府和医疗机构提供资源分配建议，优化医疗资源配置。在偏远地区，GPT作为在线智囊，为基层医生提供即时指导。 然而，GPT的应用也面临数据隐私、模型准确性、技术门槛、医疗资源不均衡及医疗责任等挑战。

Acute respiratory distress syndrome (ARDS) is characterized by increased alveolar capillary permeability and hypoxemia, often leading to multi-organ failure. Early recognition and intervention, especially the optimization of mechanical ventilation, restricted volume control, treatment of anti-inflammation, and some new type of therapies, such as prone-position ventilation and ECMO, can significantly shorten ICU stays, reduce healthcare costs and improve patient survival. In order to optimize the diagnosis and treatment of ARDS, it is necessary to integrate research results, clinical guidelines and practical experience to build a systematic knowledge system. As a smart tool, GPT has shown great potential in the medical field. It can efficiently search medical databases, build knowledge graphs, develop online platforms, and provide personalized recommendations to help doctors quickly grasp the latest progress. At the same time, GPT can also generate high-quality education and training materials to meet the training needs of different medical staff. In the online training, GPT combines simulated cases and VR/AR technology to create an immersive learning environment and improve the diagnosis and treatment capabilities of grassroots doctors. GPT can also enable remote diagnosis and treatment, especially in low-resource settings, to accelerate the treatment process through remote diagnosis and assistance. In terms of clinical decision support, GPT can analyze electronic medical records, provide early warning and intervention recommendations, and customize personalized treatment plans. It also fosters multidisciplinary collaboration and technical exchange. In terms of resource allocation, GPT can analyze data and provide resource allocation suggestions for governments and medical institutions to optimize the allocation of medical resources. In remote areas, GPT serves as an online think tank, providing immediate guidance to grassroots doctors. However, the application of GPT also faces challenges such as data privacy, model accuracy, technical thresholds, imbalance of medical resources, and medical liability.