On July 10th, the first Health Data Science Symposium of RUC was held, with over three hundred participants discussing the theme of "Theories, Methods, and Applications of Data Science in the Field of Health and Medical Care."
Lin Shangli, President of RUC, Wang Songling, Academician of the Chinese Academy of Sciences and Dean of the National Research Institute of Health Medical Big Data at Capital Medical University, and Mao Qun'an, member of National Health Commission, attended and delivered speeches. The opening ceremony of the symposium was presided over by Wang Yi, Vice President of RUC.
Lin Shangli, President of RUC, stated that the Health Big Data Research Institute, as one of the first innovative highlands of the university, aims to build an important talent center in the field of health big data and to become an internationally first-class platform in this field. With the goal of solving China's practical problems, it will construct an independent knowledge system in the field of health big data.
Lin also expressed that the university is committed to cultivating top scholars with international reputation, exploring interdisciplinary talent training models, and focusing on leveraging its unique advantages in the field of health China and related areas, thus contributing to the development of health data science and the realization of the goals of the "Healthy China" strategy.
Wang Songling, Academician of the Chinese Academy of Sciences and Dean of the National Research Institute of Health Medical Big Data at Capital Medical University, pointed out that health medical big data is a precious resource reflecting the health status of the whole population and contains huge application value. He said that RUC has long been committed to leveraging its disciplinary advantages to serve the strategic needs of national health medical big data.
He also said that the two sides have previously signed a cooperation agreement to carry out a series of cooperation in student training, scientific research, and course co-construction, and have produced cross-disciplinary research results serving the needs of the "Healthy China" strategy. Finally, he expressed hope that the two sides will further cooperate with each other, improve the level of social medical services, and solve major problems in the development of medicine.
Mao Qun'an, member of National Health Commission, stated that it is necessary to vigorously promote the empowerment of big data, artificial intelligence, and other technologies in the field of medical and health services to promote the high-quality development of the health industry. The conference, with the theme of "Theories, Methods, and Applications of Data Science in the Field of Health," carries out extensive discussions, which is of great significance.
He also said that in the future, it is possible to increase the research and innovation efforts of "Data Science + Medical Health," optimize the allocation of medical and health resources, improve service effects, reshape the management and service models of medicine and health, and innovate the integrated services of prevention, diagnosis, and rehabilitation.
Du Peng, Former Vice President of RUC, Dean of the School of Population and Health, and Dean of the Healthy China Research Institute, Professor Hu Feifang from George Washington University, and Professor Lin Xihong from Harvard University respectively made keynote speeches on the construction of "Healthy China" , clinical trial design and causal inference, and the construction of an end-to-end large-scale interpretable data science ecosystem.
The symposium set up three parallel sub-forums, with participants from the fields of health, disease prevention and control, biomedicine, and clinical research discussing topics such as "Integration of Medical Practice and Big Data Technology," "Value Application of Medical Non-structured Data," and "Data Science Challenges in Pharmaceutical Research and Development".
This symposium focuses on the latest strategic development direction in the field of intersection between health care and data science, builds a communication platform for methods and applications of health data science, and has made a positive contribution to the development of health data science by promoting interdisciplinary exchanges and cooperation.
