Literature mining for the diagnostic procedures of osteoporosis
No Thumbnail Available
Date
2011
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Open Access Color
OpenAIRE Downloads
OpenAIRE Views
Abstract
In this paper, we highlight the importance of osteoporosis disease in terms of medical research and healthcare and we consider a knowledge discovery approach regarding the diagnostic procedures of osteoporosis from a historical perspective. Osteoporosis is characterized by low bone mass, micro-architectural deterioration of bone tissue, and increased bone fragility and susceptibility to fracture. Osteoporosis affects an estimated 75 million people in Europe, the USA and Japan, with 10 million people suffering from osteoporosis in the United States alone. Osteoporosis may significantly affect life expectancy and quality of life and is a component of the frailty syndrome. We use a freely available biomedical search engine based on text-mining technology to extract the diagnostic procedures used in osteoporosis from MEDLINE articles. We conclude that there are some changes in diagnostic procesures in the last four decades and Dual energy x-ray absorptiometry is the most commonly used technique today. © 2011 Springer-Verlag Berlin.
Description
Keywords
Biomedical Text Mining, Diagnostic Procedure, Information Extraction, Osteoporosis
Turkish CoHE Thesis Center URL
Fields of Science
Citation
0
WoS Q
Scopus Q
Q3
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011 -- 25 November 2011 through 26 November 2011 -- Graz -- 87469
Volume
7058 LNCS
Issue
Start Page
43
End Page
51