Purpose/Significance To summarize the application progress of artificial intelligence (AI) in the field of digestive endoscopy, to analyze the key challenges and look forward to future trends, so as to provide guidance for clinical practice and research. Method/Process Domestic and international literature databases such as PubMed, Web of Science, and CNKI are retrieved. The application research of AI in the auxiliary diagnosis, process optimization and treatment precision of digestive endoscopy is sorted out. Result/Conclusion Although AI has significant clinical value in the field of digestive endoscopy, its application still faces major challenges, and its prospects and limitations need to be further discussed.

Purpose/Significance To build an evaluation index system of hospital intelligence in line with China's national conditions,so as to provide references for the quantitative evaluation of the degree of hospital intelligence,and to help the orderly development of hospi-tal intelligence construction.Method/Process Based on the review of the existing evaluation standard system of hospital informatization con-struction,Delphi method and analytic hierarchy process are used to discuss the construction process of hospital intelligence evaluation index system from four processes:construction of an evaluation index system,selection of experts in letter consultation,evaluation of indicator im-portance and verification of letter consultation results,and determination of the evaluation index weight.Result/Conclusion The construc-tion of hospital intelligence evaluation index system,which includes 3 first-level indexes,8 second-level indexes and 33 third-level in-dexes,is complementary to the existing evaluation system of smart hospitals,can reflect the construction foundation and development goals of the current intelligent hospitals,and has certain applicability and guidance for the future construction of smart hospitals.

Purpose/Significance To construct the conceptual model of hospital intelligence index,so as to lay the foundation for the quantitative evaluation of hospital intelligence degree,and help the intelligent construction of hospital.Method/Process The paper intro-duces the connotation of intelligence,expounds the evaluation standard system of hospital informatization construction,and considers the application of intelligence in hospital from the perspective of structure-function-effect.Result/Conclusion The conceptual model of hospital intelligence index is built.That conceptual model includes 3 first-level indicators,8 second-level indicators and 33 third-level indicators of intelligence basis,intelligence capacity and intelligence effect.As a tool for continuous improvement of medical serv-ices,regular assessment of hospital intelligence level can promote the improvement of medical quality and patient experience,and help the high-quality development of hospitals.

Purpose/Significance To thoroughly discuss and comprehensively summarize the present situation of smart hospital construction at home and abroad,the evaluation system of smart hospital in China and its future development trend.Method/Process By combing and stud-ying relevant literature,the paper summarizes the main contents of the intelligent construction of hospitals in China,systematically analyzes the construction of the intelligent evaluation index system of hospitals in China,and forecasts the development and evaluation prospects of the intel-ligent development of hospitals in combination with the reform and development trend of health undertakings in China.Result/Conclusion Hospitals in China should also develop in the direction of advanced intelligence,strengthen the overall platform building of smart hospitals,deep mining of medical big data and deep integration of medical artificial intelligence(AI),and the intelligent evaluation index system should be improved in time with the development of technology,so as to better guide the construction of smart hospitals and provide patients with more quality services.

Purpose/Significance To construct a Chinese medical knowledge Q&A corpus dataset as a standardized evaluation bench-mark for large language models(LLMs)in the medical domain,so as to improve the accuracy and efficiency of LLMs in handling Chinese medical questions.Method/Process Chinese medical paper knowledge,medical terminology explanations and supplementary questions are acquired from the Chinese medical licensing examination,and open-source Chinese medical Q&A datasets are encompassed in the developed Q&A datasets.Result/Conclusion The Chinese medical knowledge Q&A corpus datasets enrich the sources of existing datasets and promote the objective and comprehensive quantitative evaluation of large models in the medical field.In the near future,additional data such as electronic medical records and those from online health communities will be used to strengthen the support of artificial intelli-gence for the Healthy China strategy.

Purpose/Significance To explore the attitudes,willingness and influencing factors of Chinese doctors towards medical ar-tificial intelligence(AI).Method/Process A cross-sectional survey is conducted by distributing closed-ended questionnaires via We-Chat to 327 doctors.The questionnaire content includes the doctors'background,their understanding of AI,their level of acceptance,and their willingness to use it.Descriptive statistics,inter-group comparison and logistic regression analysis are used.Result/Conclu-sion Most doctors have a positive attitude towards AI,and there are differences in the willingness to use AI based on factors such as gen-der and level of attention.

Purpose/Significance To explore the construction pathway of an intelligent automation model tailored for primary health-care institutions,aiming to address the issue of repetitive reporting.Method/Process Through methods such as on-site investigations and expert consultations,a field study is conducted in primary healthcare institutions in Dongcheng District,Beijing.Utilizing information resource planning methods and data integration and mapping technologies,the business interactions and information flow within these in-stitutions are analyzed to investigate the construction pathway of an automated reporting model.Result/Conclusion The business flow and data flow are mapped out by the modeling process,a repository of relevant reporting indicators is organized,and a multi-source data au-tomatic mapping model and rules are developed.The study provides a feasible reference pathway for realizing intelligent reporting in pri-mary healthcare institutions.

Purpose/Significance To understand the correlation of multi-source evaluation indicators for highly cited papers in medi-cal universities in different databases,and to provide references for the discovery,utilization and evaluation of literature resources.Meth-od/Process The paper takes the highly cited papers of Capital Medical University from 2013 to 2023 as the research object,analyzes 38 e-valuation indexes in H1 Connect,Dimensions,ESI,Web of Science,InCites and SciVal,and makes correlation analysis from representative indicators,patent and policy citation indicators,browse and use indicators,relative indicators,journal indicators,cited frequency and Alt-metric indicators.Result/Conclusion It is found that the similar indicators in each group have relatively high correlation,individual indicators such as peer-reviewed weighted sum of stars and Weibo mentions have no significant correlation with most different platform indicators.

Purpose/Significance To conduct a cross-metric analysis of citations and cited references of highly cited medical infor-matics articles in the first quartile of the journal citation reports(JCR)over the past 10 years,and to analyze the sources of citing disci-plines and the origins of cited disciplines.Method/Process The screened data is divided into citation literature data and citing literature data.Statistics are performed from the perspective of secondary disciplines,and the general analysis is carried out from the perspective of first-level disciplines.The measurement indicators are set as discipline diversity,discipline balance,discipline continuity and disci-pline interdisciplinarity,which are analyzed respectively from the perspectives of citations and citing.Result/Conclusion The interdisci-plinary characteristics of medical informatics include a wide range of disciplines involved,consistent and stable external influence,and a tendency towards certain cross-disciplinary objects,and on this basis,the suggestions for disciplinary development are proposed.

Purpose/Significance To analyze the technical situation of patent owners in the field of clinical decision support system(CDSS)in China as a whole,so as to provide references for CDSS related technical research.Method/Process Firstly,the CDSS patent data are analyzed from the aspects of application trend,patent disclosure,technology field distribution,etc.,then the patentees are di-vided into different categories,and their technical concerns are analyzed by word frequency and interword vector.Finally,the technology correlation and patent exclusives are analyzed based on the active patentees.Result/Conclusion The number of CDSS patent disclosure shows an overall increasing trend.This field has not formed a technological monopoly in China.Government departments and research in-stitutions should pay attention to the possible financial risks.