Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.
Stud Health Technol Inform
; 150: 579-83, 2009.
Article
en En
| MEDLINE
| ID: mdl-19745377
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.
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Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Calidad de Vida
/
Traumatismos de la Médula Espinal
/
Bases del Conocimiento
Tipo de estudio:
Prognostic_studies
Límite:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2009
Tipo del documento:
Article
País de afiliación:
España