Diving Deeper into Models

Alberto Traverso, Frank Dankers, Akuli B. Osong, Leonard Wee, Sander van Kuijk

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic


Pre-requisites to better understand the chapter: knowledge of the major steps and procedures of developing a clinical prediction model. Logical position of the chapter with respect to the previous chapter: in the last chapters, you have learned how to develop and validate a clinical prediction model. You have been learning logistic regression as main algorithm to build the model. However, several different more complex algorithms can be used to build a clinical prediction model. In this chapter, the main machine learning based algorithms will be presented to you. Learning objectives: you will be presented with the definitions of: machine learning, supervised and unsupervised learning. The major algorithms for the last two categories will be introduced.
Original languageEnglish
Title of host publicationFundamentals of Clinical Data Science
EditorsPieters Kubben, Michel Dumontier, Andre Dekker
Number of pages13
ISBN (Electronic)978-3-319-99713-1
ISBN (Print)978-3-319-99712-4
Publication statusPublished - 2019

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