A0278 - Machine learning-based survival model optimizes the outcome prediction in high-grade T1 bladder carcinoma: Improving selection of suitable candidates for timely radical cystectomy.
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| Title: | A0278 - Machine learning-based survival model optimizes the outcome prediction in high-grade T1 bladder carcinoma: Improving selection of suitable candidates for timely radical cystectomy. |
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| Authors: | Subiela Henriquez, J.D. (AUTHOR), Krajewski, W. (AUTHOR), Gonzalez-Padilla, D.A. (AUTHOR), Basile, G. (AUTHOR), Moschini, M. (AUTHOR), Montorsi, F. (AUTHOR), Aumatell, J. (AUTHOR), Gallioli, A. (AUTHOR), Minguez, C. (AUTHOR), Gomez Rivas, J. (AUTHOR), Nowak, Ł. (AUTHOR), Contieri, R. (AUTHOR), D' Andrea, D. (AUTHOR), Afferi, L. (AUTHOR), Pradere, B. (AUTHOR), Soria, F. (AUTHOR), Mertens, L.S. (AUTHOR), Tully, K. (AUTHOR), Cimadamore, A. (AUTHOR), Laukhtina, E. (AUTHOR) |
| Source: | European Urology. Feb2023:Supplement 1, Vol. 83, pS399-S400. 2p. |
| Database: | Academic Search Ultimate |
| ISSN: | 03022838 |
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| DOI: | 10.1016/S0302-2838(23)00327-5 |
