基于医学本体的语义融合系统在生物医学信息学中的应用

R. Teodorescu, C. Cernazanu-Glavan, V. Cretu, Daniel Racoceanu
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引用次数: 7

摘要

统一医学语言系统(UMLS)为计算机辅助诊断系统(CADS)提供了使用注释医学术语的可能性。提出了一种新的基于UMLS的语义融合系统。该融合系统可用于诊断神经退行性疾病的CADS。由于UMLS元辞典包含了大量的数据,所以对我们使用的数据进行分类和提取是必要的。为此,我们使用了一种前馈神经网络,它既能训练消极模式,也能训练积极模式。在语义层面,我们生成了一个三层的网络结构,这使我们有可能添加医学知识,以便将数据聚类并为融合过程做好准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of the medical ontology for a semantic-based fusion system in biomedical informatics Application to Alzheimer disease
The unified medical language system (UMLS) offers the possibility to use annotated medical terms for computer aided diagnoses system (CADS). We present a new semantic fusion system, based on UMLS. This fusion system has applications on a CADS that diagnoses neurodegenerative diseases. Since the UMLS Metathesaurus contains a huge amount of data, classification and extraction of the data we use is necessary. For this purpose, we use a feedforward neural network which is capable of training the negative patterns as well as the positive ones. At the semantic level we generate a three-layered network structure, which gives us the possibility of adding medical knowledge in order to cluster the data and prepare it for the fusion process.
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