构建统一医学知识图谱，融合基因与病历数据提升癌症诊疗理解
Toward a Unified Graph-Based Representation of Medical Data for Precision Oncology Medicine
- 用知识图谱整合基因数据与临床记录
- 将医疗任务转化为可高效求解的计算机科学问题
- 适合精准肿瘤学与医学数据融合研究者
我们提出一种新的统一图表示方法，通过独特的知识图谱整合患者基因信息、临床记录与医学知识。该方法能推断出仅靠单一数据源无法获得的有意义信息与解释。系统性地管理多个数据库并构建知识图谱，为深入理解肿瘤学提供了新视角。我们还将一些有用的医疗任务转化为理论计算机科学中的经典问题，利用现有高效算法解决。
原文摘要 · Abstract (English)
We present a new unified graph-based representation of medical data, combining genetic information and medical records of patients with medical knowledge via a unique knowledge graph. This approach allows us to infer meaningful information and explanations that would be unavailable by looking at each data set separately. The systematic use of different databases, managed throughout the built knowledge graph, gives new insights toward a better understanding of oncology medicine. Indeed, we reduce some useful medical tasks to well-known problems in theoretical computer science for which efficient algorithms exist.
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