Efficacy Analysis in Clinical Trials an Update

Efficacy Analysis in an Era of Machine Learning

Efficacy Analysis in Clinical Trials an Update

Efficacy Analysis in an Era of Machine Learning

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Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to even out multiple variables

Modern medical computer files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required

This is the first publication of clinical trials that have been systematically analyzed with machine learning. In addition, all of the machine learning analyses were tested against traditional analyses. Step by step statistics for self-assessments are included

The authors conclude, that machine learning is often more informative, and provides better sensitivities of testing than traditional analytic methods do




Preface

Traditional and Machine-Learning Methods for Efficacy Analysis.- Optimal-Scaling for Efficacy Analysis.- Ratio-Statistic for Efficacy Analysis.- Ratio-Statistic for Efficacy Analysis
Complex-Samples for Efficacy Analysis.- Bayesian-Networks for Efficacy Analysis.- Evolutionary-Operations for Efficacy Analysis.- Automatic-Newton-Modeling for Efficacy Analysis.- High-Risk-Bins for Efficacy Analysis.- Balanced-Iterative-Reducing-Hierarchy for Efficacy Analysis.- Cluster-Analysis for Efficacy Analysis.- Multidimensional-Scaling for Efficacy Analysis.- Binary Decision-Trees for Efficacy Analysis.- Continuous Decision-Trees for Efficacy Analysis.- Automatic-Data-Mining for Efficacy Analysis.- Support-Vector-Machines for Efficacy Analysis.- Neural-Networks for Efficacy Analysis.- Ensembled-Accuracies for Efficacy Analysis.- Ensembled-Correlations for Efficacy Analysis.- Gamma-Distributionsfor Efficacy Analysis.- Validation with Big Data, a Big Issue
Index.


ISBN 978-3-030-19920-3
Artikelnummer 9783030199203
Medientyp Buch
Auflage 1st ed. 2019
Copyrightjahr 2020
Verlag Springer, Berlin
Umfang XI, 304 Seiten
Abbildungen XI, 304 p. 295 illus., 44 illus. in color.
Sprache Englisch