Titlebook: Machine Learning in Medicine; Ton J. Cleophas,Aeilko H. Zwinderman Textbook 2013 Springer Science+Business Media Dordrecht 2013 cluster an

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Time-Dependent Predictor Modeling,Individual patients’ predictors of survival may change across time, because people may change their lifestyles. Standard statistical methods do not allow adjustments for time-dependent predictors. In the past decade time-dependent factor analysis has been introduced as a novel approach adequate for the purpose.

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Seasonality Assessments,Seasonal patterns are assumed in many fields of medicine. However, biological processes are full of variations and the possibility of chance findings can often not be ruled out.

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Non-linear Modeling,Novel models for the assessment of non-linear data are being developed for the benefit of making better predictions from the data.

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Artificial Intelligence, Multilayer Perceptron Modeling,Back propagation (BP) artificial neural networks is a distribution-free method for data-analysis based on layers of artificial neurons that transduce imputed information. It has been recognized to have a number of advantages compared to traditional methods including the possibility to process imperfect data, and complex nonlinear data.

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Hierarchical Cluster Analysis for Unsupervised Data,Drug efficacy is multifactorial and with multiple variables regression modeling rapidly looses power and it is invalid if the correlations between the variables is strong. Hierarchical cluster analysis can handle hundreds of variables, and is unaffected by strong correlations.

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