Biomedical Informatics Ontology System (BIOS)

Medical knowledge graph is by nature a semantic network that reveals relationships among objects of health and medical care and offers a formalized description of objects in reality and their interrelationships. It is built on a man-made professional knowledge base, with continuous expansion of objects and relationships through algorithms and human review. It encompasses medical concepts including diseases, symptoms, medications, surgeries and non-surgical treatments, and a variety of medical relationships. 

Medical knowledge graph is the core of medical AI. We will dedicate to developing the world’s largest open-source medical knowledge graph and drive its application in a broad range of health and medical scenarios. This project is led by Yutao Xie, Director of Engineering at International Digital Economy Academy (IDEA), and a number of experts in the medical AI field. Based on large-scale medical text data, the team taps into a diversity of data resources using natural language processing and text mining technologies. They collaborate with relevant global institutions and make full use of the supercomputing cluster in IDEA that ranks among the top 50 globally to build a medical knowledge graph that covers all subjects.