EAGER: Medical Knowledge Graph Construction from Heterogeneous Sources

本项目的目标是构建全面的医学知识图谱。这样的知识图谱可以满足用户对可靠医疗信息日益增长的需求，有助于患者和医生之间的有效沟通，并可能有助于降低高昂的医疗保健成本。该项目解决了在医学领域观察到的一系列独特的挑战，并开发了有效的方法，可以从众包数据的洪流中提取知识，以增强医学知识图谱。本课题从以下几个角度对医学知识图的构建问题进行了研究：1)在医疗问答网站的噪声中提取可靠的医学事实的过程中，有效地考虑了医学术语之间的语义关系；2)在医学知识发现过程中，设计了一个统一的框架来集成来自不同数据源的信息；3)根据图中医学术语之间的现有关系，通过推理新的关系来完成知识图的构建。所提出的研究被实现在一个系统原型中，该原型显示所提取的医疗事实和知识图，从而为寻求医疗信息的在线用户提供帮助。建议的技术用于改进教育方法。该项目的研究成果被整合到课程材料和项目中，以加强学生的培训。

The objective of this project is to construct comprehensive medical knowledge graphs. Such knowledge graphs can satisfy users' growing needs for reliable medical information, help the effective communication between patients and doctors, and potentially help reduce the high costs of health care. This project tackles a series of unique challenges observed in medical domains, and develops effective approaches that can extract knowledge from the deluge of crowdsourced data to augment medical knowledge graphs. The proposed research advances the fields of knowledge graph construction and information trustworthiness analysis by developing novel methods that mines knowledge from unstructured data in medical domains.This project investigates the problem of medical graph construction from the following perspectives: 1) Effective approaches are developed to take into account the semantic relations between medical terms during the extraction of reliable medical facts from noisy answers on healthcare question and answering websites; 2) A unified framework is designed to integrate information from heterogeneous data sources in the process of medical knowledge discovery; 3) The knowledge graph is completed by inferring new relations based on existing relations between medical terms in the graph. The proposed research is implemented into a system prototype that displays the extracted medical facts and the knowledge graph, which benefit online users who seek medical information. The proposed techniques are used to enhance educational methodologies. Research results of this project are integrated into course materials and projects that reinforce student training.