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Energy Spectrum Scanning of Thyroid Nodules:A Study Based on Support Vector Machine / 中国医学影像学杂志
Chinese Journal of Medical Imaging ; (12): 231-234,240, 2015.
Article Dans Chinois | WPRIM | ID: wpr-600471
ABSTRACT
PurposeSupport vector machine (SVM) is a machine learning method based on statistical learning theory of Vapnik-Chervonenkis (VC) dimension structure and risk minimization theory. We analyzed the gem spectrum CT scan data of patients with thyroid nodules and established the SVM diagnostic model. The experimental targets were then reduced and the forecast analysis was carried out based on SVM model. The diagnostic model and experimental methods were proved to provide guidance for clinical diagnosis of thyroid nodules.

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Guide de pratique langue: Chinois Texte intégral: Chinese Journal of Medical Imaging Année: 2015 Type: Article

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Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Guide de pratique langue: Chinois Texte intégral: Chinese Journal of Medical Imaging Année: 2015 Type: Article