Preparing Data for Predictive Modelling

Sander van Kuijk*, Frank Dankers, Alberto Traverso, Leonard Wee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

This is the first chapter of five that cover an introduction to developing and validating models for predicting outcomes for the individual patient. Such prediction models can be used for predicting the occurrence or recurrence of an event, or of the most likely value on a continuous outcome. We will mainly focus on the prediction of binary outcomes, such as the occurrence of a complication, recurrence of disease, the presence of metastases, remission, survival, etc. This chapter deals with the selection of an appropriate study design for a study on prediction, and on methods to manipulate the data before the statistical modelling can begin.
Original languageEnglish
Title of host publicationFundamentals of Clinical Data Science
EditorsPieters Kubben, Michel Dumontier, Andre Dekker
PublisherSpringer
Chapter6
Pages75-84
Number of pages10
ISBN (Electronic)978-3-319-99713-1
ISBN (Print)978-3-319-99712-4
DOIs
Publication statusPublished - 2019

Fingerprint

Dive into the research topics of 'Preparing Data for Predictive Modelling'. Together they form a unique fingerprint.

Cite this