Using machine learning tools to predict prostate cancer upgrading after robotic radical prostatectomy
| Autor: | Andrea Fuschi, L. Dutto, A. Boudewijn, Antonio Luigi Pastore, Andrea Tubaro, Manuela Mattioli, Eric Medvet, Riccardo Lombardo, S. Saccani, C. De Nunzio, Joern H. Witt, Daniele Panfilo, Pietro Tortella, Antonio Carbone |
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| Přispěvatelé: | EAU, Panfilo, Daniele, De Nunzio, C., Pastore, A. L., Saccani, S., Boudewijn, A., Tortella, P., Mattioli, M., Lombardo, R., Carbone, A., Fuschi, A., Dutto, L., Witt, J. H., Medvet, E., Tubaro, A. |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
genetic structures
Prostatectomy business.industry Urology medicine.medical_treatment 030232 urology & nephrology machine learning prostate cancer Nomogram Machine learning computer.software_genre medicine.disease 03 medical and health sciences Prostate cancer 0302 clinical medicine 030220 oncology & carcinogenesis medicine Artificial intelligence business computer |
| Popis: | INTRODUCTION AND OBJECTIVES:Several nomograms have been developed to predict prostate cancer upgrading however very little artificial intelligence (AI) tools are available for this purpose. Aim of ... |
| Databáze: | OpenAIRE |
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