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Clinical Prediction Models and
Machine Learning (WK80)

The purpose of a prediction model is to estimate the probability of the presence of a particular outcome as accurately as possible. Prediction models are often developed with clinical practice in mind, and involve combining information about individual patients to calculate an individual’s probability of illness or recovery. The model can then be presented in the form of a clinical predictive rule. General applicability – i.e. the accuracy of the prediction model when applied to new patients in the future – is another very important aspect.

Course details

Date:
25, 26, 29, 30 January 2024
Tuition fee:
1.395
City: Amsterdam Course coordinator: M.W. (Martijn) Heymans, PhD
Language: English Learning method: Lectures and computerpractical
Examination: Written exam with computer assignments (facultative) Examination dates: See page Exams
Number of EC: 2 Details: Contact hours: 24
Date Tuition fee:
25, 26, 29, 30 January 2024
1.395
City: Amsterdam
Course coordinator: M.W. (Martijn) Heymans, PhD
Language: English
Learning method: Lectures and computerpractical
Examination: Written exam with computer assignments (facultative)
Examination dates: See page Exams
Number of EC: 2
Details: Contact hours: 24

About the course

Clinical Prediction Models and Machine Learning is a 4-days course. he course consists of an intensive programme of partly interactive lectures, combined with computer-based practical work. Examples taken from clinical practice will be used for the computer-based work.

If a course is [Full], you can still register, but you will be placed on a waiting list. We will contact you as soon as a place becomes available. At that time you can still decide whether you want to participate in the course.

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