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Comparison of models to predict clinical failure after radical prostatectomy.

Comparison of models to predict clinical failure after radical prostatectomy.

http://www.wikidata.org/entity/Q37339685

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Reporting performance of prognostic models in cancer: a review.Postoperative prostate-specific antigen nadir improves accuracy for predicting biochemical recurrence after radical prostatectomy: Results from the Shared Equal Access Regional Cancer Hospital (SEARCH) and Duke Prostate Center databases.Positive surgical margins at radical prostatectomy predict prostate cancer specific mortality Prostate Cancer: Utility of Whole-Lesion Apparent Diffusion Coefficient Metrics for Prediction of Biochemical Recurrence After Radical Prostatectomy.Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip.Prostate cancer: Could sensitive PSA assays expedite salvage radiotherapy?New Prognostic Markers: The Pathway from Research to Clinical Practice

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Comparison of models to predict clinical failure after radical prostatectomy.

http://www.wikidata.org/entity/Q37339685

description

article científic

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article scientifique

@fr

articolo scientifico

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artigo científico

@pt

bilimsel makale

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scientific article published on January 2009

@en

vedecký článok

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vetenskaplig artikel

@sv

videnskabelig artikel

@da

vědecký článek

@cs

name

Comparison of models to predict clinical failure after radical prostatectomy.

@en

Comparison of models to predict clinical failure after radical prostatectomy.

@nl

type

label

Comparison of models to predict clinical failure after radical prostatectomy.

@en

Comparison of models to predict clinical failure after radical prostatectomy.

@nl

prefLabel

Comparison of models to predict clinical failure after radical prostatectomy.

@en

Comparison of models to predict clinical failure after radical prostatectomy.

@nl

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Comparison of models to predict clinical failure after radical prostatectomy.

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Angel M Serio

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David Verbel

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Faisal M Khan

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Fernando J Bianco

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Michael J Donovan

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Peter T Scardino

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Scott E Eggener

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Valentina Bayer-Zubek

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Victor E Reuter

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P2860

Knowledge-based analysis of microarray gene expression data by using support vector machines

Time-dependent ROC curves for censored survival data and a diagnostic marker.

Natural history of progression after PSA elevation following radical prostatectomy.

Preoperative PSA velocity and the risk of death from prostate cancer after radical prostatectomy.

Use of nomograms to predict the risk of disease recurrence after definitive local therapy for prostate cancer.

Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy

When and how to use informatics tools in caring for urologic patients.

Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy.

Preoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy

What is a support vector machine?

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303-310

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scholarly article

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10.1002/CNCR.24016

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2

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115

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Carlos Cordon-Cardo

Andrew J Vickers

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2009-01-01T00:00:00Z

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23489923

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19025977

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2740715

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