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www.thedoctors.com/KnowledgeCenter/Publications/TheDoctorsAdvocate/CON_ID_002961, accessed on 18/2/2013.
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2
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Ethical and legal issues in the use of clinical decision support systems
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Berner, E.S.1
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BMC, Against quantiles: Categorization of continuous variables in epidemiologic research, and its discontents
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C. Bennette and A. Vickers BMC, Against quantiles: categorization of continuous variables in epidemiologic research, and its discontents, Medical Research Methodology, 12:21, 2012.
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Medical Research Methodology
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Bennette, C.1
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Clinical decision support programs can be risky business
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J Healthc Inf Manag
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Klein, S.R.1
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Model transparency and validation: A report of the ISPOR-SMDM modeling good research practices task force-4
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Value Health
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Eddy, D.M.1
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A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology
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V. Van Belle, B. Van Calster, D. Timmerman, T. Bourne, C. Bottomley, L. Valentin, P. Neven, S. Van Huffel, J.A.K. Suykens and S. Boyd, A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology', PLoS ONE, 7(3): 1-10., 2012.
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PLoS ONE
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Interval coded scoring systems for survival analysis
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Villmann, T.1
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A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue
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IEEE Transactions On Neural Networks
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Etchells, T.A.1
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How to find simple and accurate rules for viral protease cleavage specificities
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T. Rögnvaldsson, T. A. Etchells, L. You, D. Garwicz, I. H. Jarman and P. J. G. Lisboa, How to find simple and accurate rules for viral protease cleavage specificities, BMC Bioinformatics, 10:149, 2009.
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Lisboa, P.J.G.6
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Efficient identification of independence networks using mutual information
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DOI 10.1007/s00180-012-0320-6
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D. Bacciu, T. A. Etchells, P. J. G. Lisboa and J. Whittaker, Efficient identification of independence networks using mutual information, Computational Statistics DOI 10.1007/s00180-012-0320-6, 2012.
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Computational Statistics
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Bacciu, D.1
Etchells, T.A.2
Lisboa, P.J.G.3
Whittaker, J.4
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A structure independent algorithm for causal discovery
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T. Claassen and T. Heskes. A structure independent algorithm for causal discovery. In ESANN'11, pages 309-314.d-side pub., 2011.
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A constraint-based approach to incorporate prior knowledge in causal models
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G. Borboudakis, S. Triantafilou, V. Lagani and I. Tsamardinos A constraint-based approach to incorporate prior knowledge in causal models. In ESANN'11, pages 303-308.d-side pub., 2011.
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NHS North West Commissioned Report by the North West Public Health Observatory, May
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H. Carlin, I. H. Jarman, S. Chambers, P. J. G. Lisboa, S. Knuckey, C. Perkins and M. A. Bellis 'North West Mental Wellbeing Survey - what influences wellbeing?', NHS North West Commissioned Report by the North West Public Health Observatory, May 2011.
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North West Mental Wellbeing Survey - What Influences Wellbeing?
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Carlin, H.1
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Lisboa, P.J.G.4
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Villmann, T.1
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84887043005
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Seeing is believing: The importance of visualization in real-world machine learning applications
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A. Vellido, J. D. Martín, F. Rossi, and P. J. G. Lisboa. Seeing is believing: The importance of visualization in real-world machine learning applications. In ESANN'11, pages 219-226.d-side pub., 2011.
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Vellido, A.1
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Lisboa, P.J.G.4
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Neighborhood Graph for Clinical Case Retrieval and Decision Support
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Semisupervised classification with cluster regularization
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R. G. F. Soares, H. Chen and X. Yao, Semisupervised classification with cluster regularization, IEEE Tran Neural Networks and Learning Systems, 23(11):1779-1792, 2012.
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Soares, R.G.F.1
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A principled approach to network-based classification and data representation
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H. Ruiz, T. A. Etchells, I. H. Jarman, J. D. Martín, and P. J. G. Lisboa, A principled approach to network-based classification and data representation, accepted for Neurocomputing, 2013.
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Accepted For Neurocomputing
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Ruiz, H.1
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Jarman, I.H.3
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Making machine learning models interpretable
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A. Vellido, J. D. Martín, and P. J. G. Lisboa. Making machine learning models interpretable. In ESANN'12, pages 163-172. d-side pub., 2012.
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