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  • / Clinical analysis of optimized neural network risk models to predict clinically significant prostate cancer and avoid unnecessary prostate biopsies.

Clinical analysis of optimized neural network risk models to predict clinically significant prostate cancer and avoid unnecessary prostate biopsies.

Abstract Poster

Authors

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Christopher J.D. Wallis

Division of Urology and Surgical Oncology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON, Canada

Christopher J.D. Wallis , Robert J Paproski , Desmond Pink , Catalina Vasquez , Adrian S. Fairey , M Eric Hyndman , Armen G. Aprikian , Adam Kinnaird , Perrin Beatty , Christian P. Pavlovich , Leonard S. Marks , John D Lewis

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Poster Details

Meeting

2023 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Genitourinary Cancer—Prostate, Testicular, and Penile

Track

Genitourinary Cancer—Prostate, Testicular, and Penile

Sub Track

Biologic Correlates

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr 5023)

DOI

10.1200/JCO.2023.41.16_suppl.5023

Abstract #

5023

Poster Bd #

117

Abstract Disclosures

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