Stratification of malignant renal neoplasms from cystic renal lesions using deep learning and radiomics features based on a stacking ensemble CT machine learning algorithm

Using nephrographic phase CT images combined with pathology diagnosis, we aim to develop and validate a fusion feature-based stacking ensemble machine learning model to distinguish malignant renal neoplasms from cystic renal lesions (CRLs). This retrospective research includes 166 individuals with C...

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Detalles Bibliográficos
Autores principales: He, Quan-Hao, Tan, Hao, Liao, Fang-Tong, Zheng, Yi-Neng, Lv, Fa-Jin, Jiang, Qing, Xiao, Ming-Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640984/
https://www.ncbi.nlm.nih.gov/pubmed/36387261
http://dx.doi.org/10.3389/fonc.2022.1028577

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640984/
https://www.ncbi.nlm.nih.gov/pubmed/36387261
http://dx.doi.org/10.3389/fonc.2022.1028577

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