Neuro-fuzzy modeling: an accurate and interpretable method for predicting bladder cancer progression. von Catto, J, Abbod, M, Linkens, D, Hamdy, F

Predictive modeling in cancer: where systems biology meets the stock market. von Abbod, M, Hamdy, F, Linkens, D, Catto, J

Comparative study of intelligent models for the prediction of bladder cancer progression. von Abbod, M, Linkens, D, Catto, J, Hamdy, F

Designing power system stabilizer for multimachine power system using neuro-fuzzy algorithm von Othman, M. F., Mahfouf, M., Linkens, D. A.

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Artificial intelligence for the prediction bladder cancer von Abbod, M, Catto, J, Chen, M, Linkens, D, Hamdy, F

Neurofuzzy modeling to determine recurrence risk following radical cystectomy for nonmetastatic urothelial carcinoma of the bladder. von Catto, J, Abbod, M, Linkens, D, Larré, S, Rosario, D, Hamdy, F

Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks. von Catto, J, Linkens, D, Abbod, M, Chen, M, Burton, J, Feeley, K, Hamdy, F

Development of a prognostic marker panel in bladder cancer using aberrant promoter methylation von Catto, J, Yates, D, Rehman, I, Meuth, M, Abbod, M, Linkens, D, Hamdy, F

Promoter hypermethylation identifies progression risk in bladder cancer. von Yates, DR, Rehman, I, Abbod, M, Meuth, M, Cross, S, Linkens, D, Hamdy, F, Catto, J

Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of non invasive papillary bladder cancer progression von Wild, P, Catto, J, Abbod, M, Linkens, D, Herr, A, Pilarsky, C, Wissmann, C, Hamdy, F, Hartmann, A

Artificial intelligence re-analysis of gene array data identifies novel markers of urothelial cancer progression von Catto, J, Abbod, M, Linkens, D, Wild, P, Herr, A, Pilarsky, C, Wissman, C, Hartmann, A, Hamdy, F

Artificial intelligence technique for gene expression profiling of urinary bladder cancer von Abbod, M, Catto, J, Linkens, D, Wild, P, Herr, A, Wissmann, C, Pilarsky, C, Hartmann, A, Hamdy, F

Artificial intelligence technique for gene expression profiling of urinary bladder cancer von Abbod, M, Catto, J, Linkens, D, Wild, P, Herr, A, Wissmann, C, Pilarsky, C, Hartmann, A, Hamdy, F, IEEE

Artificial intelligence and bladder cancer arrays. von Wild, P, Catto, J, Abbod, M, Linkens, D, Herr, A, Pilarsky, C, Wissmann, C, Stoehr, R, Denzinger, S, Knuechel, R, Hamdy, F, Hartmann, A

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression. von Catto, J, Abbod, M, Wild, P, Linkens, D, Pilarsky, C, Rehman, I, Rosario, D, Denzinger, S, Burger, M, Stoehr, R, Knuechel, R, Hartmann, A, Hamdy, F

Suitability of PSA-detected localised prostate cancers for focal therapy: experience from the ProtecT study. von Catto, J, Robinson, M, Albertsen, P, Goepel, JR, Abbod, M, Linkens, D, Davis, M, Rosario, D, Warren, A, Varma, M, Griffiths, D, Grigor, K, Mayer, N, Oxley, J, Deshmukh, N, Lane, J, Metcalfe, C, Donovan, J, Neal, D, Hamdy, F

Suitability of PSA-detected localised prostate cancers for focal therapy: Experience from the ProtecT study von Catto, J, Robinson, M, Albertsen, P, Goepel, JR, Abbod, M, Linkens, D, Davis, M, Rosario, D, Warren, A, Varma, M, Griffiths, D, Grigor, K, Mayer, N, Oxley, J, Deshmukh, N, Lane, J, Metcalfe, C, Donovan, J, Neal, D, Hamdy, F