Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques
Abstract In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging–reporting and data system (PI-RADS) is combined with clinical variables p...
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Main Authors: | Luis Mariano Esteban, Ángel Borque-Fernando, Maria Etelvina Escorihuela, Javier Esteban-Escaño, Jose María Abascal, Pol Servian, Juan Morote |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
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Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-88297-6 |
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