Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions

BACKGROUND: The rising prevalence of cystic renal lesions (CRLs) detected by computed tomography necessitates better identification of the malignant cystic renal neoplasms since a significant majority of CRLs are benign renal cysts. Using arterial phase CT scans combined with pathology diagnosis res...

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Detalles Bibliográficos
Autores principales: He, Quan-Hao, Feng, Jia-Jun, Lv, Fa-Jin, Jiang, Qing, Xiao, Ming-Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9834471/
https://www.ncbi.nlm.nih.gov/pubmed/36629980
http://dx.doi.org/10.1186/s13244-022-01349-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9834471/
https://www.ncbi.nlm.nih.gov/pubmed/36629980
http://dx.doi.org/10.1186/s13244-022-01349-7

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