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Solution for the Multivariate prediction modelling with applications in precision medicine (KI-Course)

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Multivariate prediction modelling with applications in precision medicine

This repository contains the solution for the final exam of Multivariate prediction modelling with applications in precision medicine offered by Karolinska Institute.

Aim

This course aims to provide an introduction to both supervised and unsupervised methodologies for prediction modelling with a focus on biomedical applications, molecular epidemiology and personalised medicine.

Learning outcome

After successfully completing this course you as a student are expected to be able to:

  • Perform and assess basic quality control and outlier detection
  • Apply unsupervised and supervised statistical learning methods to detect patterns in data
  • Devise cross-validation strategies for parameter estimation, model selection and prediction performance evaluation
  • Make informed judgement of how to apply basic principles for variable selection
  • Critically evaluate prediction models in real-world applications

More information for the course can be found here:

Author

  • Taner Arslan

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Solution for the Multivariate prediction modelling with applications in precision medicine (KI-Course)

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