Application of support vector machine in the detection of early cancer / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 1045-1048, 2005.
Article
em Zh
| WPRIM
| ID: wpr-238282
Biblioteca responsável:
WPRO
ABSTRACT
Support Vector Machine (SVM) is an efficient novel method originated from the statistical learning theory. It is powerful in machine learning to solve problems with finite samples. Due to the deficiency of cancer cells, character of patient and noise in the raw data, it is very difficult to diagnose early cancer accurately. In this paper, SVM is employed in detecting early cancer and the results are encouraged compared with conventional methods. The accuracy of Non-linear SVM classifier is especially high in all kinds of classifiers, which indicates the potential application of SVM in early cancer detection.
Texto completo:
1
Índice:
WPRIM
Assunto principal:
Algoritmos
/
Reconhecimento Automatizado de Padrão
/
Inteligência Artificial
/
Interpretação Estatística de Dados
/
Modelos Estatísticos
/
Redes Neurais de Computação
/
Diagnóstico Precoce
/
Diagnóstico
/
Neoplasias
Tipo de estudo:
Diagnostic_studies
/
Risk_factors_studies
/
Screening_studies
Limite:
Humans
Idioma:
Zh
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2005
Tipo de documento:
Article