Zhongshan Hospital's Clinical Research Achieves Another Major Breakthrough

Recently, the team of Li Xiaoying and Chen Ying from the Endocrinology Department of Sun Yat sen Hospital affiliated to Fudan University, together with the team of Professor Wang Guangyu from Beijing University of Posts and Telecommunications, published research results online in the international top medical journal NatureMedicine (natural medicine) - the first international proposal to adopt the AI system "RL-DITR" based on strong chemical learning algorithm to formulate insulin decision-making strategies, effectively improving the accuracy of insulin treatment programs for patients with type 2 diabetes. The research results can provide personalized and dynamic diagnosis and treatment programs for patients with type 2 diabetes, assist in establishing a hierarchical diagnosis and treatment system, and improve the efficiency of chronic disease management

Recently, the team of Li Xiaoying and Chen Ying from the Endocrinology Department of Sun Yat sen Hospital affiliated to Fudan University, together with the team of Professor Wang Guangyu from Beijing University of Posts and Telecommunications, published research results online in the international top medical journal NatureMedicine (natural medicine) - the first international proposal to adopt the AI system "RL-DITR" based on strong chemical learning algorithm to formulate insulin decision-making strategies, effectively improving the accuracy of insulin treatment programs for patients with type 2 diabetes. The research results can provide personalized and dynamic diagnosis and treatment programs for patients with type 2 diabetes, assist in establishing a hierarchical diagnosis and treatment system, and improve the efficiency of chronic disease management.

China is the largest country of diabetes. According to the latest data, one in every nine adults has diabetes. Among them, type 2 diabetes accounts for more than 90% of the total number of diabetes, and nearly 50% of patients need insulin injection treatment. How to accurately and efficiently adjust insulin dosage for such a large group of diabetes patients? This has always been a difficult problem that troubles the medical community.

Traditional insulin dose adjustment mainly relies on doctors' experience and cannot meet the demand of dynamic changes among individuals. Since 2020, Li Xiaoying and Chen Ying's team, together with Professor Wang Guangyu's team, have jointly carried out the research on AI system "RL-DITR" based on innovative algorithms such as reinforcement learning to optimize insulin treatment scheme for type 2 diabetes patients. This system can predict the optimal drug dosage in real-time based on the historical data and current physiological conditions of patients, as well as the differences in insulin response and changes in insulin demand during the progression of the disease. It can develop personalized, accurate, and dynamic treatment strategies to achieve blood sugar control goals.

Research has found that compared to other artificial intelligence models and current clinical standard protocols, RL-DITR is closer to the judgment of doctors with rich clinical experience, with a difference of only 1.2 units compared to their recommended insulin dose. At the same time, it increases the percentage of time to reach glucose (TIR) of patients by 24.1%, and does not cause adverse consequences such as severe hypoglycemia or ketoacidosis. The decision-making system is easy to operate and can automatically read and process data in real time. It is expected to be used in more extensive application scenarios such as home management of patients in the future, providing important support for refined and intelligent management of diabetes, and benefiting the majority of diabetes patients.

Gu Jianying, Secretary of the Party Committee of Zhongshan Hospital Affiliated to Fudan University, stated that building a digital medical and health world and a new ecosystem of medical services is the unremitting pursuit of Zhongshan Hospital. By deeply integrating new technologies such as 5G, artificial intelligence, big data, and digital twins with high-quality medical resources, Zhongshan Hospital aims to create the first "5G+digital twin smart medical ecosystem" in China. In the future, the full scenario application of digital twin smart healthcare will promote continuous innovation in smart healthcare related technologies, making it more convenient for the public to seek medical treatment. Based in the Yangtze River Delta, radiating all over China, and facing the world, Zhongshan Hospital will continue to build a "new paradigm" of smart hospitals with 5G as the support, and assist in the construction of a healthy China.

Zhongshan Hospital has always attached great importance to scientific research innovation, emphasizing the need to identify and propose problems from clinical practice, and solve problems through high-level and standardized scientific research. It has continuously strengthened top-level design, established a mature and efficient new technology cultivation system, clinical research management system, fruit transformation system, medical and industrial integration system, and other scientific and technological innovation models with Zhongshan characteristics. Secondly, new information technologies such as "5G, cloud, big, material, mobile and intelligent" are used to empower medical science and technology innovation, which are widely used in the diagnosis and treatment of brain diseases, liver tumors, cardiovascular diseases, diabetes, etc., to build and improve hospital data platforms and smart research platforms, and effectively improve the efficiency and quality of scientific research. In addition, Zhongshan Hospital has increased funding for clinical research, cultivated and developed a large number of research projects that can solve clinical problems, advocated for win-win cooperation, and through deep cooperation with universities, research institutes, and R&D enterprises, challenged the technical problems of "bottleneck" and "doorstep", and achieved a series of major breakthrough results.

On September 15th, Sun Yat sen Hospital affiliated with Fudan University held a press conference on major clinical research achievements in the field of endocrinology. The party secretary Gu Jianying, deputy party secretary Li Yun, director of endocrinology department Li Xiaoying, deputy researcher of endocrinology department Chen Ying and other research team members, as well as heads of relevant functional departments of the hospital, attended the conference. The press conference was presided over by Tang Qiqun, Assistant Dean of Zhongshan Hospital Affiliated to Fudan University and Executive Dean of Clinical Medical Research Institute of Zhongshan Hospital.

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