Prediction of neural tube defect using support vector machine / 生物医学与环境科学(英文)
Biomedical and Environmental Sciences
;
(12): 167-172, 2010.
Article
Dans Anglais
| WPRIM
| ID: wpr-360607
ABSTRACT
<p><b>OBJECTIVE</b>To predict neural tube birth defect (NTD) using support vector machine (SVM).</p><p><b>METHOD</b>The dataset in the pilot area was divided into non overlaid training set and testing set. SVM was trained using the training set and the trained SVM was then used to predict the classification of NTD.</p><p><b>RESULT</b>NTD rate was predicted at village level in the pilot area. The accuracy of the prediction was 71.50% for the training dataset and 68.57% for the test dataset respectively.</p><p><b>CONCLUSION</b>Results from this study have shown that SVM is applicable to the prediction of NTD.</p>
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Chine
/
Projets pilotes
/
Épidémiologie
/
Anomalies du tube neural
Type d'étude:
Étude pronostique
Limites du sujet:
Humains
Pays comme sujet:
Asie
langue:
Anglais
Texte intégral:
Biomedical and Environmental Sciences
Année:
2010
Type:
Article
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