Titlebook: Machine Learning in Medicine - Cookbook; Ton J. Cleophas,Aeilko H. Zwinderman Book 2014 The Author(s) 2014 Computer science.Data mining.Ma

Foreshadow

Partial Correlations for Removing Interaction Effects from Efficacy Data (64 Patients)The outcome of cardiovascular research is generally affected by many more factors than a single one, and multiple regression assumes that these factors act independently of one another, but why should they not affect one another. This chapter is to assess whether partial correlation can be used to remove interaction effects from linear data.

gregarious

Canonical Regression for Overall Statistics of Multivariate Data (250 Patients)To assess in datasets with multiple predictor and outcome variables, whether canonical analysis, unlike traditional multivariate analysis of variance (MANOVA), can provide overall statistics of combined effects.

烦人

dysphagia

哎呦

Correspondence Analysis for Identifying the Best of Multiple Treatments in Multiple Groups (217 PatiMultiple treatments for one condition are increasingly available, and a systematic assessment would serve optimal care. Research in this field to date is problematic.

沉思的鱼

Decision Trees for Decision Analysis (1,004 and 953 Patients)Decision trees are, so-called, non-metric or non-algorithmic methods adequate for fitting nominal and interval data. This chapter is to assess whether decision trees can be appropriately applied to predict health risks and improvements.

glacial

FISC

Machine Learning in Medicine - Cookbook978-3-319-04181-0Series ISSN 2191-544X Series E-ISSN 2191-5458

勤勉

ordain

SpringerBriefs in Statisticshttp://image.papertrans.cn/m/image/620693.jpg