As an emerging technology, artificial intelligence (AI) uses human theory and technology for robots to study, develop, learn and identify human technologies. Thoracic surgeons should be aware of new opportunities that may affect their daily practice by the direct use of AI technology, or indirect use in the relevant medical fields (radiology, pathology, and respiratory medicine). The purpose of this paper is to review the application status and future development of AI associated with thoracic surgery, diagnosis of AI-related lung cancer, prognosis-assisted decision-making programs and robotic surgery. While AI technology has made rapid progress in many areas, the medical industry only accounts for a small part of AI use, and AI technology is gradually becoming widespread in the diagnosis, treatment, rehabilitation, and care of diseases. The future of AI is bright and full of innovative perspectives. The field of thoracic surgery has conducted valuable exploration and practice on AI, and will receive more and more influence and promotion from AI.
Objective To carry out the systematic clinical management to reduce the incidence of femoral pseudoaneurysm after interventional treatment. Methods A historical controlled study was used to compare the management effect before (from October 2012 to October 2013) and after (from March 2014 to March 2015) the application of doctor-nurse integrated systematic clinical management mode. This work mode enhanced cooperation between doctors and nurses, formed the clinical path for nursing workflows and contingency plans, and strengthened specialized education and training for nurses. Results After the implementation of systematic clinical management, the incidence of femoral pseudoaneurysm was significantly lower than before (1.0% vs. 2.7%), and the difference was statistically significant (P<0.05). Conclusions The systematic clinical management, carrying out in the doctor-nurse integration mode, can improve the quality of nursing and reduce the incidence of femoral pseudoaneurysm. And the management model has achieved remarkable results. So it is worth to be applied in the clinical practices.
ObjectiveTo investigate the application and effect of doctor-nurse collaboration model for patients undergoing day surgery of laparoscopic cholecystectomy. MethodsFrom April 2010 to October 2013, we established the day-case laparoscopic cholecystectomy rapid rehabilitation team by day-surgery ward nurses, anesthesiologists, and surgeons. Collaboration was practiced through preoperative health education for the 1 902 patients, perioperative nursing cooperation, postoperative early activity and feeding of the patients, and follow-up. ResultsAfter the operation, there were 8 cases of incision bleeding, 1 case of bile leakage, 8 cases of shoulder and back pain, and 12 cases of nausea and vomiting. All the patients' postoperitive complications were controlled after treatment. ConclusionThe doctor-nurse collaboration model can significantly ensure the medical quality and safety of day surgery and improve the patients' medical experience. All the Patients, hospital and society will benefit from the model.
ObjectiveTo investigate the management methods of drug repercussion and its intervention measures in the Burn and Plastic Surgery Department by analyzing the reasons for drug repercussion. MethodBased on the drug repercussion data provided by the computer information center, we analyzed the common reasons and the status quo of drug repercussion. Active intervention measures were carried out, and real-time supervision and feedback of drug repercussion management were also performed. We compared such repercussion indexes before intervention (between May and September 2013) and after intervention (between October 2013 and February 2014):number of drug repercussion patients, times of drug repercussion, amount of money involved in drug repercussion, ratio of drug repercussion and dispensing and comprehensive ranking of the drug repercussion in the whole hospital. ResultsAfter intervention, the ranking of the causes of drug repercussion changed obviously. Changing orders casually dropped to the 3rd of the rank, and changing the department based on necessity rose from the 4th to the 2nd. All the indexes (including the times, number, and amount of money of drug of repercussion, and the ratio of repercussion and dispensing and compreheasive rank) reduced significantly (P<0.05). ConclusionsActualizing active intervention measures redounds to reducing drug repercussion, standardizing clinical use of drugs, insuring safety, and advancing the satisfaction of patients and quality of medical nursing.
Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients’ cardiopulmonary function, and management of patients outside hospital.
ObjectiveTo construct the general practice tutors’ ability system in community training bases under the background of hospital-community integrated teaching of general practice.Methods From January to April 2021, literature analysis, expert group consultation, in-depth interview and questionnaire survey were conducted to construct the grass-roots general practice tutors’ ability system, and exploratory factor analysis method was applied, using main component analysis to extract the competency elements. Results There were 4 first level indicators and 20 second level indicators in the system, among which the first level indicators were personal characteristics and professionalism, teaching and research ability, basic level clinical practice ability, and base organization management ability. Conclusion This research enriches the indicators and connotations of the general practice tutors in community training base of general practice, and provides empirical research basis for the selection, ability training and performance evaluation of tutors in community practice bases of general practice medicine.