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Li Jin
Li Jin is a core member of the Jiangsu University Key Laboratory of Intelligent Medical Image Computing and the Intelligent Medical Research Institute. He graduated from Xiamen University with a bachelor’s degree and a Ph.D. from the School of Biomedical Engineering and Instrument Science, Zhejiang University. He presided over the Youth Project of the National Natural Science Foundation of China and participated in many projects such as the National Natural Science Foundation of China, major scientific research projects of Zhijiang Laboratory, and the British NIHR scientific research projects. During the doctoral stage, he was selected into the “Zhejiang University Doctoral Graduate Academic Rising Star Program” and won honors such as Zhejiang University’s outstanding graduate students. In 2021, funded by the China Scholarship Council (CSC), he will go to the University of Oxford in the UK for joint training. The main research directions are: electronic medical record (EHR) data mining based on machine learning; clinical decision support based on graph models and large language models. Mainly committed to applying medical artificial intelligence methods to: 1) clinical intelligent decision-making; 2) patient prognosis risk assessment; 3) intelligent prevention, diagnosis and treatment of diseases, etc., so as to assist the role and value of medical big data in clinical practice.
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Jiao Yiping
Jiao Yiping, Ph.D., is currently a lecturer at the School of Artificial Intelligence at Nanjing University of Information Science & Technology, and a core member of the Jiangsu University Key Laboratory of Intelligent Medical Image Computing and the Smart Medical Research Institute. He graduated with a master’s and doctoral degree from the School of Automation of Southeast University. During his period, he received funding from the China Scholarship Council and went to the Netherlands for a year of joint training with the Computational Pathology Group of Radboud University Medical Center. His main research directions are computational pathology and machine learning. He has rich experience in histopathological full scan slice analysis. He has published six SCI papers as the first author and has authorized one invention patent. Research topics include cancer focus detection and tumor microenvironment analysis in slices of lung cancer, colorectal cancer, breast cancer, and pancreatic cancer, as well as supporting slice quality control, active learning, and staining pattern analysis and other technologies.
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