To develop a medical data asset management platform, improve the value and utilization efficiency of medical data through data standardization, capitalization and productization, and support the needs of medical treatment, scientific research, management and other aspects. The platform design includes data discovery layer, data resource layer, data asset layer, data product layer, data service layer, and general support layer. It adopts data standardization, privacy computing, blockchain evidence storage, and AI large model to realize the whole lifecycle management of data. Results The application of the platform significantly enhanced the data management efficiency and data quality of medical institutions, promoted data integration and sharing, optimized the allocation of medical resources, and accelerated medical research innovation. The construction and application of the platform have significantly enhanced the data governance ability and informatization level of medical institutions, effectively addressed issues such as data silos, inconsistent data standards, and insufficient data security and privacy protection, which can provide solid support for improving the quality of medical services and research level.

With the continuous development and application of new technologies such as big data, cloud computing,and artificial intelligence, data elements have become a key force to promote the transformation of the medical and health field and the transformation of data intelligence. The demand for converting medical data into data assets is increasingly urgent, but it is also facing severe data security challenges. Therefore, enhancing the security support capability of data assets has become an important task in the process of high-quality development of hospitals. In accordance with relevant national laws and regulations and industry standards, and with reference to the data security capability evaluation model, a tertiary Grade-A hospital built a management-technology-operation integrated data security governance and management system through a series of measures such as optimizing organizational structure, improving management system, asset sorting and classification, risk assessment, strengthening technical protection,improving operation management and control, and personnel training. This system enables the hospital to manage the security of data throughout its entire life cycle, enhances its data security protection capability, and provides a strong guarantee for the hospital to apply and share data assets and explore the value of data elements in compliance with laws and regulations.

Objective To conduct systematic research on the classification and grading of medical and health data, respond to the mandatory requirements of the "Data Security Law of the People's Republic of China", improve the efficiency and security of data management, promote the exploration of data elements, and facilitate the development of medical informatization. Methods Based on national standards such as "Information Security TechnologyGuidelines for Health and Medical Data Security" (GB/T 39725 － 2020) and "Data Security Technology Rules for Data Classification and Grading" (GB/T 43697 － 2024), a data classification and grading system suitable for the medical and health field was constructed. In line with the actual situation of the Second Affiliated Hospital of the Chinese University of Hong Kong (Shenzhen), the data was divided into two major categories: individual identity-related data and medical data, and further classified into five levels. Additionally, the research team developed a classification and grading management tool that integrates functions such as data cleaning, classification, grading, and security protection, to efficiently and accurately process large-scale data. Results Through empirical research, the effectiveness and feasibility of the data classification and grading system and management tools were verified. Conclusion Data classification and grading can not only enhance the availability of data, but also can effectively reduce the risks of data leakage and abuse. The standardized and normalized management of data can promote the interconnection and interoperability among different systems, break down information island, and drive the prosperous development of the data element market.

As an important component of data elements, medical data elements have become a significant element influencing the high-quality development of medical and healthcare industry. Through literature research and case analysis, this paper reviews the development process of healthcare and medical data elements, proposes the composition and functional positioning of the “healthcare and medical data elements circulation framework system”, elaborates on the challenges faced by healthcare and medical data elements in the three-level transformation process of “data resource data asset-data product”, and puts forward countermeasures and suggestions, aiming to provide useful references for the high-quality development of the medical and healthcare industry in the new era.

Objective To analyze the current situation of TCM data assets governance, explore its development path, realize technological implementation, so as to promote the modernization and digital transformation of traditional Chinese medicine. Methods Cutting-edge technologies such as cloud computing, big data, artificial intelligence, blockchain and privacy computing were integrated to build a secure, trustworthy and controllable data assets governance platform, and the multi-source and multi-modal Chinese medicine data were standardized, tagged, classified and graded, and intelligently applied. Results The TCM data assets management platform was established, and the large model of TCM diagnosis and treatment, digitization of ancient books, optimization of smart pharmacy and development of data products were realized, which significantly improved the service efficiency and data value of traditional Chinese medicine. Conclusion The management of TCM data assets is an important foundation to promote the modernization and internationalization of TCM. In the future, we should further strengthen technology research and application practice to maximize the utilization of TCM data assets.

Objective To construct a doctor-patient dialogue abstract generation system based on large language model, which can automatically extract and summarize key medical information from doctor-patient dialogues without any annotated data. Methods The doctor-patient dialogue data were pre-labeled with a larger-scale large language model, and then the large language model with small parameter was trained based on the pseudo-parallel data. In the reasoning stage, contextual learning method was introduced, which provided a few examples integrated with command engineering, enabling the large language model to understand the doctor-patient dialogue more accurately and generate the final summary. Results The system constructed in this study significantly outperformed the existing unsupervised summarization techniques and large language models in retaining key medical information. Conclusion The ability inheritance of the small-parameter model to the large-parameter model can be realized by using the knowledge distillation method to pre-label the doctor-patient dialogue, so as to reduce the dependence on training data and improve the generality and portability of the model.

Objective Corresponding author: JIANG Xieyuan, Email: jxy0845@sina.com To analyze the problems and difficulties in the management of official seal usage under the multi-campus operation of public hospitals, explore the digitization, networking and standardization of official seal usage management, and provide reference for the construction of the specific content of the hospital OA process under the multi-campus operation of public hospitals. Methods Taking a tertiary Grade-A general hospital in Beijing as an example, relying on the existing OA platform of the hospital and utilizing digital means, the digital management process for the use of official seals was constructed. Results The implementation of this process not only improved the communication efficiency of hospital departments using the hospital seal, but also facilitated the archiving and retrieval of documents stamped with the seal, improving the administrative efficiency of the hospital. Conclusion In the context of the multi-campus hospital development trend in public hospitals, the digital management of official seals usage in public hospitals based on the OA platform can optimize the process of official seal usage, and realize standardized operation, paperless management, whole-process supervision, inquiry and traceability, which can effectively improve the efficiency of administrative management, lay a foundation for promoting the high-quality development of public hospitals, and provide reference for the development and application of digital management of official seals usage in the multi-campus mode of public hospitals.

Objective To achieve desensitization of electronic medical documents during sharing, and to protect patient privacy. Methods A lexical analyzer for medical data integrating multiple machine learning models was constructed to sort out Chinese word segmentation, part-of-speech tagging, and named entity recognition corpora in the field of medical and healthcare. Sensitive information in electronic medical documents was identified by using natural language processing technologies such as Hidden Markov Models and Conditional Random Fields and built-in sensitive information signature library, and dynamic desensitization was realized through result set streaming processing technology. Results The algorithm model has a good effect on the processing of routine sensitive personal information, with an average time of detection and desensitization of sensitive personal information was milliseconds. Conclusion The method of natural language processing with sensitive information signature library can realize the recognition and real-time desensitization of sensitive information in unstructured electronic medical documents.

Objective To use a standardized and scientific performance evaluation mechanism to dynamically monitor and evaluate family doctor contract services, so as to strengthen the connotation of contract services, expand contract coverage, increase service supply, implement health management of contracted residents, and continuously improve the service experience of contracted residents. Methods The indicator performance evaluation system was used to dynamically monitor and evaluate the contracted services of family doctors, and the work of family doctors was stimulated and constrained. Results The efficient management of community operations was achieved by means of service process reengineering, resource allocation optimization, dynamic monitoring and evaluation. Conclusion Through the in-depth promotion of family doctor contract service, operational management can be transformed into value creation, and high-quality development of community health can be promoted.

Objective To improve the security and encryption efficiency of medical image transmission in multidisciplinary treatment mode, a fast medical image encryption algorithm is proposed. Methods The encryption algorithm uses the cross scrambling method to displace the pixel positions of the image, calculates the initial value of the chaotic map using the original image hash value, and performs two pixel value permutation and diffusion in case of calculating the chaotic sequence once. Results The experimental results showed that all the security indicators achieved the expected effect. The encryption time for brain image, lumbar image, and chest image was 155.6 ms, 155.8 ms and 156.1 ms, respectively. The decryption time is 52.3 ms, 56.8 ms, and 64.4 ms, respectively. Conclusion The encryption algorithm has high security and fast operation speed, which can improve the safety and efficiency of medical image transmission in MDT diagnosis and treatment mode, and promote the development of MDT diagnosis and treatment mode from a technical perspective.

Objective To explore the application effect of large language model in the diet management of for aircrew with hyperuricemia during convalescence. Methods Using Tongyi Qianwen 2.5 as the testing model, and a registered dietitian was invited to quantitatively score the sample diet according to the "Dietary Guidelines for Adults with Hyperuricemia and Gout (2024 Edition)", and the correlation, difference and consistency of the two scores were analyzed. Requirements such as limiting the types of ingredients and restricting the total calorie intake were set, and a large language model was used to develop a daily diet plan for aircrew with hyperuricemia. The NASA-TLX self assessment scale was used to evaluate the cognitive load level of dietitians using the LLM to assist them in formulating recipes. Results Spearman rank correlation test showed that the correlation coefficient between the two scores was 0.716 (P＜0.001). Wilcoxon signed rank test showed no significant difference between the two scores (P=0.739). Bland Altman analyzed that the 95% consistency limit of the difference between the two scores was -2.699 ～ 2.975, t=0.638, P=0.526, indicating a good consistency. LLM can accurately generate daily recipes according to task characteristics. The cognitive load of dietitians completing recipe-making tasks was significantly reduced with the assistance of LLM. Conclusion LLM shows great practical effect and application potential in the diet management for aircrews with hyperuricemia, providing strong support for the rapid development of personalized diet planning.

Objective To establish a confidence classification model of virus meningitis, so as to provide valuable reference for clinical decision-making. Methods The viral meningitis data were utilized as research samples in this study, with the singular mapping underlying algorithm of Neural Network (NN) and K-Nearest Neighbor (KNN) serving as Conformal Prediction (CP), so as to establish the confidence model of viral meningitis, namely CP-NN and CP-KNN.Results The CP-NN model performed excellently when the confidence level was set to 0.998, achieving the accuracy of 0.964, the precision of 0.969, the recall rate of 0.981, and the F1 score of 0.975. Conclusion As an auxiliary diagnostic model for viral meningitis disease, CP-NN can address the issue of personalized high-risk assessment and the degradation of traditional machine learning model in diagnosis. Additionally, the prediction results are accompanied with confidence, aligning the diagnosis of viral meningitis more closely with medical needs.

Objective To sort out and analyze the current research status of medical AI in China from the perspectives of theme recognition and development and evolution, so as to provide reference for scholars to carry out related research. Methods First, relevant literatures in the field of medical AI in China from 2012 to 2023 were obtained from the three databases of CNKI, Wanfang data and CQVIP, and then the research theme and development trends in the field of medical AI were explored by using BERTopic model. Results The research themes covered the whole chain from basic medical research to clinical practice, reflecting the discipline’s complexity and multi dimensionality. The core direction focuses on medical education and fundamental research, clinical technological innovation, medical data mining, and public health management. Divergent trends in research hotspots were observed, and the research on medical images, network models and medical AI education are popular, while precision medicine and medical data mining demonstrate latent potential for growth. Conclusion This study clarifies the subject dynamics and emerging frontiers in medical AI, offering reference for optimizing the subject layout, guiding resource investment and promoting technological translation.

Medical insurance plays an important role in chronic disease management. By sorting out and summarizing the relevant policies on the application of digital technology in chronic disease management in China, discussing the application of digital therapy in the field of chronic disease at home and abroad, and its medical insurance payment policy, medical insurance development suggestions for chronic disease digital therapy are proposed, aiming to provide perfect support for the digital development of chronic disease management in China.

Objective To improve the quality of single-disease reporting data, reduce the burden on doctors, and improve the diagnosis and treatment effect. Methods Build an intelligent single-disease reporting and quality control platform, sort out the detailed items in the reporting forms of each disease from the service system, and the platform uniformly captures and fills them in to complete the reporting. Collate the quality control indicators of single-disease reporting to organize and analyze the reported data. Results The application of the platform significantly improved the data management efficiency and data quality of medical institutions, promoted the integration and sharing of data, optimized the allocation of medical resources, and accelerated the innovation of medical research. Conclusion The construction and application of the platform have significantly enhanced the data governance ability and informatization level of medical institutions, effectively solved the problems of data islands, inconsistent data standards, insufficient data security and privacy protection, and provided solid support for improving the quality of medical services and scientific research.

Objective To analyze the research hotspots and trends in the field of Internet medical applications in recent ten years. Methods Using "Internet medical" "Internet hospital" "Internet diagnosis and treatment" “Telemedicine” as keywords, the literature related to Internet medical application in recent ten years was searched in CNKI database. Bicomb 2.0 was used to count the word frequency of keywords and establish the discourse matrix and co-occurrence matrix. SPSS 26.0 was used for cluster analysis and multi-dimensional scale analysis. It also analyzed the literature content of Internet medical applications. Results A total of 5,470 related literatures were retrieved, and through cluster analysis and multi-dimensional scale analysis, it is found that the research hotspots of Internet medical care are hierarchical diagnosis and treatment, medical consortiums, artificial intelligence, etc. Through content analysis of the literature, it is found that the research on Internet medical application focuses on the diagnosis and treatment of chronic and common diseases, and there are more research related to Internet medical auxiliary services. The elderly and women, children and young people are important service targets of Internet medical care. Conclusion It is necessary to clarify and broaden the scope of disease types of Internet medical services, emphasize the construction of Internet healthcare diagnosis and treatment services, and develop user-friendly Internet medical care for population groups, such as the elderly, women, children and young people, so as to benefit more people.

Objective To propose a data-driven predictive maintenance method for hospital medical equipment failure records, so as to optimize equipment management strategies. Methods Effective fault records of medical equipment in a hospital were collected and cleaned. Weibull distribution was used to model the fault interval data of each equipment, and the Maximum Likelihood Estimate method was used to fit the model parameters. The Kolmogorov-Smirnov (K-S) test was then employed to screen out models that fit the actual distribution. Finally, the Mean Time Between Failures (MTBF) and the failure probability of each device were calculated based on the failure interval distribution model. Results A dynamic database for equipment failure prediction was established, which included features such as failure probabilities of each device. By the end of 2023, 99.63% of all medical equipment in the hospital had failure intervals consistent with the Weibull distributions. Conclusion The model based on Weibull distribution can effectively reflect the distribution characteristics of failure interval of each medical equipment, and are of great significance for making reasonable predictive maintenance strategies for medical equipment.