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.


“You are how you read”, says Dr. Harry Shum, Chair of Board, International Digital Economy Academy (IDEA).

Reading good papers and read papers well are the first step proposed by Dr. Harry Shum for the cognitive model of paper reading and the foundation to effectively improve the ability for topic selection and research and to produce good papers. The paper reading platform ReadPaper has been set up on such a back drop, providing necessary support for paper reading in practice. Led by Yutao Xie, Director of Engineering at IDEA, the project is being iterated and improved continuously based on the existing Beta version. They use and strengthen the thesis knowledge graph and improve product experience based on user feedback to provide a platform for the learning and exchange of global researchers.

Currently, ReadPaper garners nearly 200 million papers written by 270 million authors from nearly 30,000 universities and research institutes, covering almost all subjects of mankind. Scientific research would be impossible to conduct without the help of papers, and it is a very challenging problem with regard to how to understand papers and read papers well. Hence, our mission is “to make all papers in the world easy to read”.

Team Introduction

  • Yutao Xie - Director of Engineering at International Digital Economy Academy (IDEA)

    Yutao Xie serves as Director of Engineering in International Digital Economy Academy (IDEA). He previously worked in Microsoft as a Partner engineer and the managing Director of Microsoft (China) Operating Systems Group. During his 20+ years of service in Microsoft, Yutao Xie served various positions in Microsoft including Microsoft Office Product Team, Bing Team, Search Technology Center as well as Microsoft China’s Operating Systems Group, Cloud and AI division. He has extensive technical and managerial experience in operating systems technologies, search technologies, AI, cloud, Applications and services fields.