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Reply from Authors re: David J. DeGraff. Novel Use of a Combined Artificial Intelligence Approach to Identify Patients with Noninvasive Urothelial Cell Carcinoma of the Urinary Bladder Who Are at Greatest Risk for Progression to Muscle-Invasive Disease: A Step Forward. Eur Urol 2010; 57: 407-8

Publication status:: Published

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APA Style

Catto, J., & Hamdy, F. (2010). Reply from Authors re: David J. DeGraff. Novel Use of a Combined Artificial Intelligence Approach to Identify Patients with Noninvasive Urothelial Cell Carcinoma of the Urinary Bladder Who Are at Greatest Risk for Progression to Muscle-Invasive Disease: A Step Forward. Eur Urol 2010; 57: 407-8. EUROPEAN UROLOGY, 57(3), 408–409.

MLA Style

Catto, J, and F Hamdy. “Reply from Authors Re: David J. DeGraff. Novel Use of a Combined Artificial Intelligence Approach to Identify Patients with Noninvasive Urothelial Cell Carcinoma of the Urinary Bladder Who Are at Greatest Risk for Progression to Muscle-Invasive Disease: A Step Forward. Eur Urol 2010; 57: 407-8.” EUROPEAN UROLOGY, vol. 57, no. 3, 2010, pp. 408–09.

Chicago Style

Catto, J, and F Hamdy. 2010. “Reply from Authors Re: David J. DeGraff. Novel Use of a Combined Artificial Intelligence Approach to Identify Patients with Noninvasive Urothelial Cell Carcinoma of the Urinary Bladder Who Are at Greatest Risk for Progression to Muscle-Invasive Disease: A Step Forward. Eur Urol 2010; 57: 407-8.” EUROPEAN UROLOGY 57 (3): 408–9.
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Publisher copy:: 10.1016/j.eururo.2009.11.043

Authors

+ Catto, J More by this author

Role:: Author

+ Hamdy, F More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Engineering Science
Sub department:: Institute of Biomedical Engineering
Role:: Author

Journal:: EUROPEAN UROLOGY More from this journal
Volume:: 57
Issue:: 3
Pages:: 408-409
Publication date:: 2010-03-01
DOI:: 10.1016/j.eururo.2009.11.043
ISSN:: 0302-2838

Language:: English
Pubs id:: pubs:120844
UUID:: uuid:f070b525-acda-4bb3-a201-e46d469db246
Local pid:: pubs:120844
Source identifiers:: 120844
Deposit date:: 2012-12-19
ARK identifier:: ark:/29072/ora_f070b525acda4bb3a201e46d469db246

Terms of use

Copyright date:: 2010

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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