Paper Info
Title
TPLUFIB-WEB: A fuzzy linguistic Web system to help in the treatment of low back pain problems
Abstract
Low back pain affects a large proportion of the adult population at some point in their lives and has a major economic and social impact. To soften this impact, one possible solution is to make use of Information and Communication Technologies. Recommender systems, which exploit past behaviors and user similarities to predict possible user needs, have already been introduced in several health fields. In this paper, we present TPLUFIB-WEB, a fuzzy linguistic Web system that uses a recommender system to provide personalized exercises to patients with low back pain problems and to offer recommendations for their prevention. This system may be useful to reduce the economic impact of low back pain, help professionals to assist patients, and inform users on low back pain prevention measures. TPLUFIB-WEB satisfies the Web quality standards proposed by the Health On the Net Foundation (HON), Official College of Physicians of Barcelona, and Health Quality Agency of the Andalusian Regional Government, endorsing the health information provided and warranting the trust of users.
Year
DOI
Venue
2014
10.1016/j.knosys.2014.03.004
Knowl.-Based Syst.
Keywords
Field
DocType
health care,fuzzy linguistic modeling,low back pain,recommender systems,quality evaluation
Health care,Recommender system,Population,Economic impact analysis,Computer science,Knowledge management,Information and Communications Technology,Linguistics,Low back pain,The Internet,Government
Journal
Volume
ISSN
Citations 
67,
0950-7051
8
PageRank 
References 
Authors
0.44
19
5
Name
Order
Citations
PageRank
Bernabé Esteban1101.16
Álvaro Tejeda-Lorente2977.88
Carlos Porcel345024.12
Manolo Arroyo480.44
Enrique Herrera-Viedma513105642.24