Artificial intelligence for the prediction bladder cancer

Artificial intelligence for the prediction bladder cancer

New techniques for the prediction of tumour behaviour are needed as statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. We have previously shown that the predictive accuracies of neuro-fuzzy modelling (NFM...

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Bibliografiske detaljer
Main Authors:	Abbod, M, Catto, J, Chen, M, Linkens, D, Hamdy, F
Format:	Journal article
Sprog:	English
Udgivet:	2004

Lignende værker

Comparative study of intelligent models for the prediction of bladder cancer progression.
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Artificial intelligence technique for gene expression profiling of urinary bladder cancer
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Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of non invasive papillary bladder cancer progression
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Promoter hypermethylation identifies progression risk in bladder cancer.
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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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Neurofuzzy modeling to determine recurrence risk following radical cystectomy for nonmetastatic urothelial carcinoma of the bladder.
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Development of a prognostic marker panel in bladder cancer using aberrant promoter methylation
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Artificial intelligence re-analysis of gene array data identifies novel markers of urothelial cancer progression
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Less is more: artificial intelligence and gene-expression arrays.
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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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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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Differential expression of hMLH1 and hMSH2 is related to bladder cancer grade, stage and prognosis but not microsatellite instability.
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Comparing gene promoter methylation frequencies in urine from patients with bladder cancer with urine from non-cancerous young and elderly control patients
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An evaluation of urinary microRNA reveals a high sensitivity for bladder cancer
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An evaluation of urinary microRNA reveals a high sensitivity for bladder cancer.
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Aberrant promoter methylation in pre-malignant and invasive tumours of the urinary bladder
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A gene promoter hypermethylation panel to detect transitional cell carcinoma of the bladder
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Artificial neural network in predicting bladder cancer recurrence
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Hypermethylation of CpG islands and shores around specific microRNAs and mirtrons is associated with the phenotype and presence of bladder cancer.
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Hypoxia regulated miRNAs in bladder cancer
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MicroRNA in prostate, bladder, and kidney cancer: A systematic review
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MicroRNA in prostate, bladder, and kidney cancer: a systematic review.
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