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Review

Diving Deeper into Models

Alberto Traverso  1 , Frank J. W. M. Dankers  1   2 , Biche Osong  1 , Leonard Wee  1 , Sander M. J. van Kuijk  3
Pieter Kubben  1 , Michel Dumontier  2 , Andre Dekker  3
, editors.
In: Fundamentals of Clinical Data Science [Internet]. Cham (CH): Springer; 2019. Chapter 9.
.
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Review

Diving Deeper into Models

Alberto Traverso et al.
Free Books & Documents

Excerpt

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.

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References

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