Gerardo Lagunes García, Lucía Prieto Santamaría, Eduardo P. García del Valle, M. Zanin, Ernestina Menasalvas Ruiz, A. R. González
{"title":"维基百科疾病文章:其内容和演变分析","authors":"Gerardo Lagunes García, Lucía Prieto Santamaría, Eduardo P. García del Valle, M. Zanin, Ernestina Menasalvas Ruiz, A. R. González","doi":"10.1109/CBMS.2019.00136","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":311634,"journal":{"name":"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Wikipedia Disease Articles: An Analysis of their Content and Evolution\",\"authors\":\"Gerardo Lagunes García, Lucía Prieto Santamaría, Eduardo P. García del Valle, M. Zanin, Ernestina Menasalvas Ruiz, A. R. González\",\"doi\":\"10.1109/CBMS.2019.00136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":311634,\"journal\":{\"name\":\"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2019.00136\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2019.00136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wikipedia Disease Articles: An Analysis of their Content and Evolution
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.