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Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states
dc.contributor.author | Gibert, Karina |
dc.contributor.author | García Rudolph, A. |
dc.contributor.author | Curcoll, Lluïsa |
dc.contributor.author | Soler, Dolors |
dc.contributor.author | Pla, Laura |
dc.contributor.author | Tormos, José Maria |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa |
dc.date.accessioned | 2010-07-16T10:12:10Z |
dc.date.available | 2010-07-16T10:12:10Z |
dc.date.created | 2009-08-01 |
dc.date.issued | 2009-08-01 |
dc.identifier.citation | Gibert, C. [et al.]. Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states. "Studies in health technology and informatics", 01 Agost 2009, vol. 150, p. 579-583. |
dc.identifier.issn | 0926-9630 |
dc.identifier.uri | http://hdl.handle.net/2117/8203 |
dc.description.abstract | In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains. |
dc.format.extent | 5 p. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències |
dc.subject.lcsh | Data mining |
dc.subject.lcsh | Decision support systems |
dc.subject.lcsh | Knowledge management |
dc.subject.lcsh | Spinal cord |
dc.subject.lcsh | Quality of life |
dc.title | Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states |
dc.type | Article |
dc.subject.lemac | Mineria de dades |
dc.subject.lemac | Decisió, Presa de |
dc.subject.lemac | Gestió del coneixement |
dc.subject.lemac | Medul·la espinal -- Ferides i lesions |
dc.subject.lemac | Qualitat de vida |
dc.contributor.group | Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic |
dc.relation.publisherversion | http://person.hst.aau.dk/ska/MIE2009/papers/MIE2009p0579.pdf |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 2574663 |
dc.description.version | Postprint (published version) |
local.citation.author | Gibert, C.; García, A.; Curcoll, L.; Soler, D.; Pla, L.; Tormos, J. |
local.citation.publicationName | Studies in health technology and informatics |
local.citation.volume | 150 |
local.citation.startingPage | 579 |
local.citation.endingPage | 583 |
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