Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient’s Pathological Grades

PURPOSE: To evaluate the value of multiple machine learning methods in classifying pathological grades (G1,G2, and G3), and to provide the best machine learning method for the identification of pathological grades of pancreatic neuroendocrine tumors (PNETs) based on radiomics. MATERIALS AND METHODS:...

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Detalles Bibliográficos
Autores principales: Zhang, Tao, Zhang, YueHua, Liu, Xinglong, Xu, Hanyue, Chen, Chaoyue, Zhou, Xuan, Liu, Yichun, Ma, Xuelei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905094/
https://www.ncbi.nlm.nih.gov/pubmed/33643890
http://dx.doi.org/10.3389/fonc.2020.521831

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905094/
https://www.ncbi.nlm.nih.gov/pubmed/33643890
http://dx.doi.org/10.3389/fonc.2020.521831

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