A rough set method to treat ECG signals for predicting coronary heart disease / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 1025-1028, 2008.
Article
en Zh
| WPRIM
| ID: wpr-342690
Biblioteca responsable:
WPRO
ABSTRACT
In this paper is used the rough set theory to deal with the information contained in electrocardiographic waveforms and to find out the correlation between coronary heart disease (CHD) and the selected indices in electrocardiographic lead I. The principles of attribute reduction are applied, the redundancy of a decision-making table is reduced, and the important characters and diagnostic rules are extracted. The real case analysis shows that clear and concise diagnostic rules can be established by using rough set theory, which can be helpful to the clinical diagnosis of CHD.
Texto completo:
1
Índice:
WPRIM
Asunto principal:
Algoritmos
/
Toma de Decisiones Asistida por Computador
/
Procesamiento de Señales Asistido por Computador
/
Valor Predictivo de las Pruebas
/
Enfermedad Coronaria
/
Diagnóstico
/
Electrocardiografía
/
Métodos
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
Zh
Revista:
Journal of Biomedical Engineering
Año:
2008
Tipo del documento:
Article