Significance of GPT to empower the diagnosis and treatment of ARDS

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.

Key Words: generative pre-trained transformers; acute respiratory distress syndrome; extracorporeal membrane oxygenation