With the continuous development of critical care medicine, the survival rate of critical ill patients continues to increase. However, the residual dysfunction will have a far-reaching impact on the burden on patients, families, and health-care systems, and will significantly increase the demand of the follow-up rehabilitation treatment. Critical illness rehabilitation intervenes patients who are still in the intensive care unit (ICU). It can prevent complications, functional deterioration and dysfunction, improve functional activity and quality of life, shorten the time of mechanical ventilation, the length of ICU stay and hospital stay, and also reduce medical expenses. Experts at home and abroad believe that early rehabilitation of critical ill patients is safe and effective. So rehabilitation should be involved in critical ill patients as early as possible. However, the promotion of this model is still limited by the setting of safety parameters, the ICU culture, the lack of critical rehabilitation professionals, and the physiological and mental cognitive status of patients. Rehabilitation treatment in ICU is constantly being practiced at home and abroad.
Objective To analyze the hot spot and future application trend of artificial intelligence technology in the field of intensive care medicine. Methods The CNKI, WanFang Data, VIP and Web of Science core collection databases were electronically searched to collect the related literature about the application of artificial intelligence in the field of critical medicine from January 1, 2013 to December 31, 2022. Bibliometrics was used to visually analyze the author, country, research institution, co-cited literature and key words. Results A total of 986 Chinese articles and 4 016 English articles were included. The number of articles published had increased year by year in the past decade, and the top three countries in English literature were China, the United States and Germany. The predictive model and machine learning were the most frequent key words in Chinese and English literature, respectively. Predicting disease progression, mortality and prognosis were the research focus of artificial intelligence in the field of critical medicine. ConclusionThe application of artificial intelligence in the field of critical medicine is on the rise, and the research hotspots are mainly related to monitoring, predicting disease progression, mortality, disease prognosis and the classification of disease phenotypes or subtypes.