Data Science in Clinical Practice

Careful data curation and analyses are essential in developing machine learning algorithms, that may usefully contribute to solving problems encountered in routine healthcare. Nevertheless, many valuable contributions never transition from the computer to the bedside. Often implementation is never attempted, or they fail to get the relevant CE marking (or equivalent local standard), or their implementation fails to elicit the intended health benefit (failure due to lack of clinical utility).

The current courses focus on the latter and provides the foundation necessary to plan and conduct clinical evaluation of machine learning solutions to fairly assess their contribution to clinical practice.

Quick overview
  • 3-4 hours
  • Self-paced and 100% flexible
  • Aimed at healthcare professionals
  • Dynamic online assignments
  • English
€79,- ex. VAT
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Course topics

Specifically, using relevant case studies you will learn:

  • A short introduction on prognostication and machine learning
  • Field usability and feasibility analyses
  • Early clinical evaluation
  • Introduction to causal inference
  • Limitations of traditional RCTs and alternative designs for clinical evaluations
  • Critical considerations of front-end-development

Check out the DATAclinic Animation Video


We are Elevate.

We believe that future-proof research is essential for good care. That is why we combine innovative medical knowledge with didactics. Thanks to our extensive network and proven didactic methods, we make Life Sciences and Health professionals better than yesterday.

Meet the team

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