Multiclassifier fusion based on radiomics features for the prediction of benign and malignant primary pulmonary solid nodules

BACKGROUND: To test the ability of a multiclassifier model based on radiomics features to predict benign and malignant primary pulmonary solid nodules. METHODS: Computed tomography (CT) images of 342 patients with primary pulmonary solid nodules confirmed by histopathology or follow-up were retrospe...

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Detalles Bibliográficos
Autores principales: Shen, Yao, Xu, Fangyi, Zhu, Wenchao, Hu, Hongjie, Chen, Ting, Li, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154443/
https://www.ncbi.nlm.nih.gov/pubmed/32309318
http://dx.doi.org/10.21037/atm.2020.01.135

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7154443/
https://www.ncbi.nlm.nih.gov/pubmed/32309318
http://dx.doi.org/10.21037/atm.2020.01.135

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