{"title":"[基于生成式人工智能的全流程疾病诊疗辅助系统的开发与应用]。","authors":"Wanjie Yang, Hao Fu, Xiangfei Meng, Changsong Li, Ce Yu, Xinting Zhao, Weifeng Li, Wei Zhao, Qi Wu, Zheng Chen, Chao Cui, Song Gao, Zhen Wan, Jing Han, Weikang Zhao, Dong Han, Zhongzhuo Jiang, Weirong Xing, Mou Yang, Xuan Miao, Haibai Sun, Zhiheng Xing, Junquan Zhang, Lixia Shi, Li Zhang","doi":"10.3760/cma.j.cn121430-20250127-00093","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":24079,"journal":{"name":"Zhonghua wei zhong bing ji jiu yi xue","volume":"37 5","pages":"477-483"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Development and application on a full process disease diagnosis and treatment assistance system based on generative artificial intelligence].\",\"authors\":\"Wanjie Yang, Hao Fu, Xiangfei Meng, Changsong Li, Ce Yu, Xinting Zhao, Weifeng Li, Wei Zhao, Qi Wu, Zheng Chen, Chao Cui, Song Gao, Zhen Wan, Jing Han, Weikang Zhao, Dong Han, Zhongzhuo Jiang, Weirong Xing, Mou Yang, Xuan Miao, Haibai Sun, Zhiheng Xing, Junquan Zhang, Lixia Shi, Li Zhang\",\"doi\":\"10.3760/cma.j.cn121430-20250127-00093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":24079,\"journal\":{\"name\":\"Zhonghua wei zhong bing ji jiu yi xue\",\"volume\":\"37 5\",\"pages\":\"477-483\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Zhonghua wei zhong bing ji jiu yi xue\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3760/cma.j.cn121430-20250127-00093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Zhonghua wei zhong bing ji jiu yi xue","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3760/cma.j.cn121430-20250127-00093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
[Development and application on a full process disease diagnosis and treatment assistance system based on generative artificial intelligence].
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.