构建医疗知识图谱融合多源信息，提升救援决策准确性。
Comparing Knowledge Source Integration Methods for Optimizing Healthcare Knowledge Fusion in Rescue Operation
- 基于知识图谱整合多源医疗数据，实现跨场景知识融合。
- 提出多种概念模型，支持救援中实时决策所需的知识调用。
- 适合医疗智能系统研发者与急救场景决策支持研究者。
在医学与医疗领域，结合医学知识与患者健康信息的医疗专长应用，是关乎患者生死的关键挑战。医疗治疗与操作知识的复杂性与多样性，要求建立统一方法来汇聚、分析并利用现有知识，以实现精准的患者驱动决策。一种实现途径是融合多个医疗知识源。这使医务人员能够从多个上下文对齐的知识源中选择，从而支持关键决策。本文提出多种基于知识图谱结构的医疗知识融合概念模型，评估知识融合的实现方式，并展示如何将多种知识源整合到知识图谱中，以支持救援行动中的决策需求。
原文摘要 · Abstract (English)
In the field of medicine and healthcare, the utilization of medical expertise, based on medical knowledge combined with patients' health information is a life-critical challenge for patients and health professionals. The within-laying complexity and variety form the need for a united approach to gather, analyze, and utilize existing knowledge of medical treatments, and medical operations to provide the ability to present knowledge for the means of accurate patient-driven decision-making. One way to achieve this is the fusion of multiple knowledge sources in healthcare. It provides health professionals the opportunity to select from multiple contextual aligned knowledge sources which enables the support for critical decisions. This paper presents multiple conceptual models for knowledge fusion in the field of medicine, based on a knowledge graph structure. It will evaluate, how knowledge fusion can be enabled and presents how to integrate various knowledge sources into the knowledge graph for rescue operations.
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