Objective To analyze the international research results of artificial intelligence in the medical field by the double clustering method,and to explore the hot trends in the topic field.Meth-ods The Web of Science core collection database was searched for the research literature of artificial intelligence in the field of medicine,and the high-frequency keywords were extracted by Co-Occur-rence13.4 to generate the word matrix.The gCluto1.0 clustering toolkit was used for the double cluster analysis.Results A total of 7 803 articles were included,and the annual number of publications showed an overall upward trend.The United States ranked the first in the total number of publications.A total of 30 high-frequency subject words were extracted to form 6 clusters such as artificial intelli-gence applied to biomarker detection.The research hotspots focused on six topics:health care,disease outcome,whole-course disease monitoring,auxiliary diagnosis of cancer,model validity and differenti-al biomarkers.Conclusion Artificial intelligence has been widely used in clinical diagnosis and treat-ment technology,which provides targeted support for genetic testing and public health events.Howev-er,related domestic research is still in developing stage.In the future,we need to rely on multidisci-plinary and inter-institutional communication and cooperation to promote the development of intelligent medical in China,so that it truly becomes an important tool to promote the development of medical and health services.

Objective To analyze the international research results of artificial intelligence in the medical field by the double clustering method,and to explore the hot trends in the topic field.Meth-ods The Web of Science core collection database was searched for the research literature of artificial intelligence in the field of medicine,and the high-frequency keywords were extracted by Co-Occur-rence13.4 to generate the word matrix.The gCluto1.0 clustering toolkit was used for the double cluster analysis.Results A total of 7 803 articles were included,and the annual number of publications showed an overall upward trend.The United States ranked the first in the total number of publications.A total of 30 high-frequency subject words were extracted to form 6 clusters such as artificial intelli-gence applied to biomarker detection.The research hotspots focused on six topics:health care,disease outcome,whole-course disease monitoring,auxiliary diagnosis of cancer,model validity and differenti-al biomarkers.Conclusion Artificial intelligence has been widely used in clinical diagnosis and treat-ment technology,which provides targeted support for genetic testing and public health events.Howev-er,related domestic research is still in developing stage.In the future,we need to rely on multidisci-plinary and inter-institutional communication and cooperation to promote the development of intelligent medical in China,so that it truly becomes an important tool to promote the development of medical and health services.

Objective:To investigate the status of disaster preparedness of pediatric nurses and its influencing factors, as well as the impact path of psychological capital and perceived organizational support on disaster preparedness.Methods:This was a cross-sectional study. A total of 361 pediatric nurses from Henan Provincial People ′s Hospital, the Third Affiliated Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital were sampled from August to October 2021. They were investigated by the general information questionnaire, psychological capital questionnaire, perceived organizational support questionnaire and disaster preparedness questionnaire. SPSS25.0 was used to analyze the questionnaire and scale data, and AMOS23.0 was used to construct a structural equation model about the disaster preparedness of pediatric nurses. Results:The scores of disaster preparedness from pediatric nurses was 4.65 ± 0.92. The level of disaster preparedness was significantly positively correlated with psychological capital and perceived organizational support ( r=0.690, 0.525, both P<0.05). Disaster training and emergency drill 2 dimensions of psychological capital questionnaire (hope, resilience), perceived organizational support were independent contributing factors ( P<0.05). Psychological capital had direct effect on disaster preparedness. And the direct effect was 0.77, the indirect effect was 0.11, the total effect was 0.88, and the direct effect of perceived organizational support on disaster preparedness was 0.21. Conclusions:The score of disaster preparedness of pediatric nurses was in the middle level. Hospital managers should strengthen the training of pediatric nurses in disaster knowledge, operational and simulation exercise, pay attention to the level of nurses' psychological capital and perceived organizational support, so as to provide reference for the follow-up clinical pediatric disaster nursing education and management.

Objective:To explore the current status and influencing factors of the physiological function of patients with chronic heart failure.Methods:From January to September 2020, convenience sampling was used to select 330 patients with chronic heart failure in Fuwai Central China Cardiovascular Hospital and Henan Provincial People's Hospital as the research object. The General Information Questionnaire, Patient-Reported Outcomes Instrument for Chronic Heart Failure (CHF-PRO) , and Self-Management Scale of Heart Failure Patients were used to conduct a cross-sectional survey.Results:A total of 330 questionnaires were distributed and 315 valid questionnaires were returned. The standardized score of self-reported physiological function of patients with chronic heart failure was (54.24±16.56) . The results of multiple linear regression analysis showed that the patient's age, occupational type, drinking history, heart function classification, number of complications, heart failure diagnosis time and self-management were the influencing factors of the physiological function of patients with chronic heart failure with a statistical difference ( P<0.05) , explaining 39.6% of the total variation. Conclusions:Patients with chronic heart failure based on the patient-reported outcomes have low levels of physiological function.Clinical nursing staff should give personalized intervention guidance based on the patient's demographic and disease characteristics, so as to improve the patient's physiological function and long-term prognosis.

Objective:To summarize the management experience of helicopter medical transport in patients with critical heart disease, so as to provide reference for transport of patients with critical heart disease under the background of major natural disasters.Methods:The clinical and transport data of 36 critically ill cardiac patients in Fuwai Central China Cardiovascular Hospital from 16:30 on July 21 to 19:30 on July 22, 2021 due to historically rare heavy rainstorms were collected. All 36 critically ill cardiac patients were transported by helicopter. The safe transportation was implemented under the measures of quickly forming a transport leadership and coordination group, clarifying responsibilities and division of labor, doing a good job in the pretreatment of the patient's condition, pipeline assessment and mechanical circulation support (MCS) equipment, simulating and practicing the transfer process, improving the safety of the transfer implementation process, and effectively handing over with the target hospital. The gender, age, disease type, MCS, transport and outcome of patients were collected.Results:Thirty-six patients with cardiac critical illness were from adult extracardiac intensive care unit (ICU), adult cardiac care unit (CCU), children's CCU, comprehensive ICU and department of neurology. There were 24 males and 12 females; age (50.93±20.86) years old. There were 12 patients using respirator, 7 patients needing MCS, 2 of whom needed both extracorporeal membrane oxygenation (ECMO) and intra-aortic balloon pump (IABP), and 7 patients with post-cardiac surgery. The total distance of transportation of 36 patients was 1 638.4 km, the transit time was 10.5 hours, one way flight time of helicopter was about 8 minutes, and the average transport time per patient was about 17.5 minutes. The vital signs of 36 patients during transport were basically stable, without complications, and all of them reached the target hospital safely.Conclusion:Under the seamless connection of the rapid establishment of the transfer leadership coordination group, assessment of the patient's condition and pretreatment, the simulation of the transfer process, and the effective handover with the receiving hospital, the use of helicopter for medical transport for critically ill heart patients is feasible and safe, which can buy valuable time for saving patients' lives and further treatment.