The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

In recent years, artificial intelligence (AI) technology represented by deep learning (DL) has developed rapidly, and smart medical care has become one of the most important application areas of AI. As the most accurate noninvasive test to assess myocardial blood flow, myocardial perfusion imaging (MPI) has important clinical values. At present, the use of DL algorithms to establish learning models for MPI images is still in the research stage, and more external verification and iterative updates are needed before it can be widely used in real time clinical practice. In this article, the application of DL algorithms in MPI is comprehensively elaborated to provide a basis and direction for further research.