Annotating the Literature with Disease Ontology

作     者：YANG Li ZHOU Yanhong ZHENG Ying 

作者机构：School of Computer and Communication Engineering Changsha University of Science and Technology School of Computer Science and Technology Huazhong University of Science and Technology 

出 版 物：《Chinese Journal of Electronics》 (电子学报(英文))

年 卷 期：2017年第26卷第6期

页      面：1261-1268页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 10[医学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(No.61602060) 

主　　题：Text mining Disease ontology Annotation CRFs Dictionary Similarity 

摘      要：With the rapid growth of inquiry in biomedicine concerning diseases, the recognition of diseases becomes especially important. But only the recognition of the biomedical concepts in literature is not enough,annotations and normalizations of the concepts with normalized Metathesaurus get even more important. This paper proposes a system to annotate the literature with normalized Metathesaurus. First, a two-phase Conditional random fields(CRFs) is used to recognize the disease mentions, including the location and identification. Then, the paper adapts the Disease ontology(DO) to annotate the diseases recognized for normalization by computing the similarity between disease mentions and concepts. According to the similarities, the disease mentions are denoted as disease concepts and instances distinctively. The experiments carried out on the Arizona disease corpus show that our system makes a good achievement and outperforms the other works.