Wikipedia disease articles: an analysis of their content and evolution

被引：2

作者：

Lagunes Garcia, Gerardo ^{[1
]}

Prieto Santamaria, Lucia ^{[1
]}

Garcia del Valle, Eduardo P. ^{[2
]}

Zanin, Massimiliano ^{[1
]}

Menasalvas Ruiz, Ernestina ^{[3
]}

Rodriguez-Gonzalez, Alejandro ^{[3
]}

机构：

[1] Univ Politecn Madrid, Ctr Tecnol Biomed, Madrid, Spain

[2] Univ Politecn Madrid, ETS Ingenieros Informat, Madrid, Spain

[3] Univ Politecn Madrid, ETS Ingenieros Informat, Ctr Tecnol Biomed, Madrid, Spain

来源：

2019 IEEE 32ND INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS) | 2019年

基金：

欧盟地平线“2020”;

关键词：

wikipedia; diseases; diagnosis; wikipedia evolution; EXTRACTION;

D O I：

10.1109/CBMS.2019.00136

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Nowadays there is a huge amount of medical information that can be retrieved from different sources, both structured and unstructured. Internet has plenty of textual sources with medical knowledge (books, scientific papers, specialized web pages, etc.), but not all of them are publicly available. Wikipedia is a free, open and worldwide accessible source of knowledge. It contains more than 150,000 articles of medical content in the form of texts (non-structured information) that can be mined. The aim of this work is to study whether the evolution of information contained in Wikipedia medical articles can be used in a research context. The study has been focused on extracting the elements, from Wikipedia disease articles, that can be used to guide a diagnosis process, support the creation of diagnostic systems, or analyze the similarities between diseases, among others.

引用

页码：664 / 671

页数：8

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