Keynote Speaker

Title

Understanding Biomedical Knowledge: from Literature, Clinical Guidelines to EHRs

Abstract

Building a knowledge common is a key task in AI-powered healthcare system. Advanced Biomedical scientific studies are reported and communicated via scientific literature. Healthcare providers would follow clinical guidelines in their diagnosis and therapeutic practice. Meanwhile, clinical observations and therapeutic procedures are reported in electronic health records (EHRs). Literature, clinical guidelines and EHRs consist of meaningful and unstructured free texts, thus, text mining becomes increasingly important in biomedical research by extracting key information from free texts and converting it into a medical knowledge graph. In this talk, I will introduce efforts in medical knowledge graph constructing to help machine understand literature, clinical guidelines and EHRs.

Biography

Prof. Jiao Li serves as the Director of Center for Medical Informatics Innovation, Institute of Medical Information/Library, Chinese Academy of Medical Sciences. Dr. Li received her Ph.D. degree from the Department of Computer Science and Technology, Tsinghua University. She completed her postdoctoral training in the National Center for Biotechnology Information, National Library of Medicine, the U.S. National Institutes of Health (NCBI/NLM/NIH). Dr. Jiao Li’s research interests include medical informatics, scientific data management, and medical data mining. As a principle investigator, she has conducted studies funded by the National Key Research and Development Program of China (precision medicine), National Natural Science Foundation of China, National Population and Health Scientific Data Sharing Program of China, the Knowledge Centre for Engineering Sciences and Technology (Medical Centre), and the Key Laboratory of Knowledge Technology for Medical Integrative Publishing.