Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of non invasive papillary bladder cancer progression

Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of non invasive papillary bladder cancer progression

ग्रंथसूची विवरण
मुख्य लेखकों:	Wild, P, Catto, J, Abbod, M, Linkens, D, Herr, A, Pilarsky, C, Wissmann, C, Hamdy, F, Hartmann, A
स्वरूप:	Journal article
प्रकाशित:	2007

समान संसाधन

Artificial intelligence and bladder cancer arrays.
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प्रकाशित: (2007)

Artificial intelligence technique for gene expression profiling of urinary bladder cancer
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प्रकाशित: (2006)

Artificial intelligence technique for gene expression profiling of urinary bladder cancer
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Artificial intelligence re-analysis of gene array data identifies novel markers of urothelial cancer progression
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The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.
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Artificial intelligence for the prediction bladder cancer
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Comparative study of intelligent models for the prediction of bladder cancer progression.
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Neuro-fuzzy modeling: an accurate and interpretable method for predicting bladder cancer progression.
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Promoter hypermethylation identifies progression risk in bladder cancer.
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Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks.
द्वारा: Catto, J, और अन्य
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Application of artificial intelligence to the management of urological cancer
द्वारा: Abbod, MF, और अन्य
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Neurofuzzy modeling to determine recurrence risk following radical cystectomy for nonmetastatic urothelial carcinoma of the bladder.
द्वारा: Catto, J, और अन्य
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Development of a prognostic marker panel in bladder cancer using aberrant promoter methylation
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Predictive modeling in cancer: where systems biology meets the stock market.
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Less is more: artificial intelligence and gene-expression arrays.
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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
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Aberrant promoter methylation in pre-malignant and invasive tumours of the urinary bladder
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Invasive Intracholecystic Papillary Neoplasm of Gall Bladder with Perforation: A Case Report
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Proteomics and immunohistochemistry identify loss of nucleophosmin (B23) expression in bladder transitional cell carcinomas
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Targeting chemotherapy to advanced bladder cancer patients most likely to benefit.
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Genetic instability and transitional cell carcinoma of the bladder.
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THE HYPOXIC REGULATION OF FGFR3 IN NON MUSCLE INVASIVE BLADDER CANCER
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FGFR3 mutations indicate better survival in invasive upper urinary tract and bladder tumours.
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Role of Re-Resection in Non–Muscle-Invasive Bladder Cancer
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Metabolomics of Non-muscle Invasive Bladder Cancer: Biomarkers for Early Detection of Bladder Cancer
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Papillary and muscle invasive bladder tumors with distinct genomic stability profiles have different DNA repair fidelity and KU DNA-binding activities.
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URINARY MICRORNA IN BLADDER CANCER - A POTENTIAL DIAGNOSTIC TOOL
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The Influence of Inverted Growth Pattern on Recurrence for Patients with Non-Invasive Low Grade Papillary Urothelial Carcinoma of Bladder
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