With the integration and advancement of "Digital China" and "Healthy China" initiatives, data has become the fifth production factor after land, labor, capital, and technology. Humanity has entered the era of the digital economy. Promoting human health and well-being is crucially dependent on technological innovation in the medical and health fields. Turning to digital and smart health can advance health equity and better address global health crises.
On January 22, 2024, the fourth session of the inaugural "Global Health Development Strait Forum" titled "Digital Technology and Smart Health," invited scholars, policymakers, entrepreneurs, and other guests from different fields on both sides of the strait to explore and share cutting-edge research on digital technology and smart health. The event was chaired by Xu Ming, Associate Dean of the Institute for Global Health Development at Peking University and Dean of the Department of Global Health at the School of Public Health.
Guest Introduction:
Dong Jiahong, academic of the Chinese Academy of Engineering, President of Chang Gung Hospital, Tsinghua University, and Director of the Institute of Smart Healthcare, Tsinghua University.
Academic Dong Jiahong shared his thoughts and practices on building a regional smart health and medical service system.
The key to implementing the Healthy China imitative is transforming the medical system’s focus on disease treatment to health. Setting a goal of achieving universal health has become a pressing task for implementing medical reform in China. The new health system in China will be structured around two dimensions: strengthening grassroots and building peaks. Building peaks refers to addressing complex diseases and major medical issues through research conducted by national medical centers/regional medical centers and their collaborations with tertiary hospitals. Strengthening grassroots involves integrating urban and county-level medical institutions under the leadership of regional tertiary hospitals. Forming regional health and medical alliances can provide integrated health services covering prevention, diagnosis, treatment, rehabilitation, chronic disease management, and elderly care for all.
Health and medical alliances are a new type of medical service system that has emerged in response to the changing demands for health. These alliances focus on the health of community residents with coordination among regional medical and health institutions. This model can effectively and efficiently provide integrated services. From the current global development perspective, whether in developed countries with well-established tiered medical systems such as Japan, the UK, and the US, or in China where there are prominent contradictions in the supply and demand of medical resources, health alliances are becoming the mainstream trend in community health models. At the 2021 Beijing Municipal People's Congress, an initiative to implement pilot projects for medical alliances was passed, aiming to achieve the goals of "preventing major diseases, managing chronic diseases, treating emergencies, and promoting health." Tsinghua Chang Gung Hospital has promoted the work of the Tian Tong Yuan Health and Medical Alliance, the first large community alliance in Asia, to explore solutions to current health challenges.
Beijing Tsinghua Chang Gung Hospital is a new type of public hospital established against the backdrop of national medical reform and promoted within the Healthy China initiative. The hospital has achieved rapid and high-quality development. In its eight years of operation, with the support of the Beijing municipal government, it has become a comprehensive, well established hospital. The hospital's mission is to serve the needs of Healthy China, safeguard the health and well-being of all, develop medical science, and strive to build a distinctly Tsinghua-style teaching hospital system.
As a new type of public hospital, Beijing Tsinghua Chang Gung Hospital aims to address major medical issues and complex diseases in the country. While building a world-class medical center, it is committed to improving the level of primary health services, thus establishing a new model of clinical medical development. The hospital is located in the Tian Tong Yuan area, a community with a population of one million. Working with the Changping District government, it has selected Tianbei Street as a pilot area to establish a health alliance that provides systematic medical services for the 200,000 residents in the jurisdiction.
We have collaborated with Tsinghua University to organize a team of medical and engineering technology experts across disciplines to collaborate and propose a comprehensive health initiative with smart healthcare as the core technology.
The smart health medical solution, THIS, is the Tsinghua Smart Health Medical System. Our goal is to create a smart medical ecosystem by integrating the smart system into regional health alliances. Based on technologies such as big data, artificial intelligence, and cloud computing, the system achieves four effects: enhancing capabilities, improving efficiency, optimizing experiences, and extending services of smart health in smart medical care, services, education, and management. Looking to the future, we are confident that through the continuous exploration and development of the Tian Tong Yuan Smart Health Alliance, we will master key self-controlled technologies such as big data, artificial intelligence, and cloud computing. We will be able to form a replicable and sustainable smart health alliance model, serve a Healthy Beijing, create an innovative example of the "Healthy China" program, and establish a global innovation center for smart health medical services.
Guest Introduction:
Liu Rong, Director of the Department of Hepatobiliary and Pancreatic Surgery, Chinese People's Liberation Army General Hospital.
Professor Liu’s speech reviewed the evolution of surgery and emphasized the trend of smart surgery development. He pointed out that smart surgery has emerged with the advent of the Fourth Industrial Revolution, assisting and replacing surgical diagnosis and treatment through technologies such as artificial intelligence and machine learning. The speech covered the history of surgery, the application of smart medicine in various fields, and the theory of prognostic controlled surgery.
Professor Liu first reviewed the historical development of surgery, emphasizing the role of the Industrial Revolution in advancing surgical technology. He detailed the application of smart medicine in various aspects, including diagnosis, pathology, and surgery. Artificial intelligence has also achieved high accuracy in diagnosis, and the application of image recognition in pathology has improved the accuracy of tumor diagnosis.
Professor Liu then defined smart surgery and introduced the theory of prognostic controlled surgery. By using technologies such as neural networks, deep learning, and big data, the risk of surgical diseases can be predicted to achieve optimal treatment for patients. He elaborated on his team’s research results in pancreatic diseases and liver-biliary-pancreatic tumors surgery, introducing cases of using machine learning to improve disease diagnosis accuracy. Professor Liu also emphasized the application of digital twin technology in the surgical field, including simulation models for preoperative experimentation and planning. Finally, Professor Liu Rong shared experiences in robotic surgery. Remote surgery can be achieved through robotic platforms and address the uneven distribution of medical resources. In conclusion, he emphasized that the future development of smart surgery requires collaboration between surgeons, engineers, and enterprises.
Overall, Professor Liu’s speech systematically introduced the development process, current applications, and future trends of smart surgery. His research results not only promote innovation in surgery but also provide strong support for the development of the medical field.
Guest Introduction:
Zhou Xiang, co-founder and Co-CEO of Shanghai United Imaging Healthcare Co., Ltd.
Zhou Xiang shared his insights on artificial intelligence (AI) technology in the medical field and the current progress of United Imaging Intelligence (UII) in the field of large models. He first mentioned that prompt engineering is crucial because large models have already mastered massive knowledge. The key is to ask questions skillfully to obtain accurate answers. This shift has been reflected in many application areas. However, the complexity, ambiguity, and high risk of medicine pose challenges to the use of large model technology in the field. If we let large models generate a medical image, we may find that they will make structural errors. Even the most advanced large models still exhibit unexpected weaknesses, such as "not being able to count," and such errors or deficiencies have detrimental effects on medicine.
Zhou Xiang emphasized that the development of large model technology in the medical field should be steady and gradual. As an important strategic layout of UII in the field of artificial intelligence, UII has been focusing on empowering clinical practice, scientific research, and equipment with AI technology. Recently, the company has made phased achievements in the field of large models. Based on the multimodal characteristics of medical scenarios, the company focuses on innovation in three major directions: imaging, text, and hybrid modalities. In terms of imaging, the universality of large models enables them to perform better on tasks such as detection and segmentation. This could improve quality and efficiency in clinical scenarios such as cross-modal diagnosis and comprehensive examination. In text, the company uses open-source large models as the basis and combines them with medical knowledge for precise fine-tuning. Currently, it has focused on specific task model implementations in various clinical departments. The application prospects of hybrid modalities of medical large models are the most promising in the medical field. The company is currently implementing weakly supervised or unsupervised learning of imaging plus reports, cultivating the self-learning and self-evolution capabilities of hybrid models. This lays an innovative foundation for new application scenarios combining intra-hospital and extra-hospital data of various types and modalities in the future, thereby promoting disruptive reforms of large models in the medical field.
Zhou Xiang pointed out that large model technology is the result of intelligence "emergence." "Integration" is the key to "emergence." For the medical AI industry, "integration" can manifest as application, platform, and technology integration. Taking the major disease stroke as an example, UII's integrated solution for it has achieved breakthroughs from single applications to full-cycle and from single modality to multi-modality, achieving comprehensive coverage in clinical treatment and building a collaborative diagnosis and treatment ecosystem. UII will continue to actively promote the integration of production, education, research, and medical care.
During roundtable discussions, the following guests discussed the development of "Digital Technology and Smart Health," elaborating on their viewpoints, suggestions, and research.
· Lei Jianbo, Founding Executive Director of the Medical Informatics Center at Peking University
· Zhang Li, Chief Representative of the Asia-Pacific Medical Technology Association (APECMed) in China
· Huang Shuyan, Secretary-General of the Hospital Association of Taiwan, Secretary-General of the Asian Hospital Alliance, and Secretary-General of the Taiwan Society of Healthcare Management
· Qiao Xin, Co-founder and CEO of Deepwise
· Lv Beini, Assistant Professor at the Institute for Global Health and Development at Peking University
(Interpreted by Waverly Shi)
