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MRI index lesion radiomics and machine learning for detection of extraprostatic extension of disease: a multicenter study
OBJECTIVES: To build a machine learning (ML) model to detect extraprostatic extension (EPE) of prostate cancer (PCa), based on radiomics features extracted from prostate MRI index lesions. METHODS: Consecutive MRI exams of patients undergoing radical prostatectomy for PCa were retrospectively collec...
Autores principales: | Cuocolo, Renato, Stanzione, Arnaldo, Faletti, Riccardo, Gatti, Marco, Calleris, Giorgio, Fornari, Alberto, Gentile, Francesco, Motta, Aurelio, Dell’Aversana, Serena, Creta, Massimiliano, Longo, Nicola, Gontero, Paolo, Cirillo, Stefano, Fonio, Paolo, Imbriaco, Massimo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452573/ https://www.ncbi.nlm.nih.gov/pubmed/33792737 http://dx.doi.org/10.1007/s00330-021-07856-3 |
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