Course content

The course will give knowledge and practical experience with methods and theory for extracting, reasoning with and maintaining clinical information and knowledge. Examples and laboratory work will as far as possible be related to ongoing national or international research or development projects. Particular topics are: Standards for storage and exchange of information and knowledge; Architecture for secondary use of health data; Methods for observation, development, evaluation and analysis of information, findings, interventions, processes related to biomedical and health processes and services; Encoding and representation of clinical knowledge and information; Methods for mining, learning, processing, analysing and visualisation of clinically relevant infiormation; Systems for clinical decision support.

Learning outcome

Detailed knowledge about representations, standards and encodings.Theoretical knowledge, and practical experience, in using and adapting various methods and theories. Practical experience with selected clinical situations, data repositories and systems.

Learning methods and activities

Lectures, group project and programming laboratory.

Further on evaluation

Portfolio assessment is the basis for the grade in the course. The portfolio consists of an individual task (30%) and a group report (70%).

Both parts have to be passed in order to pass the course.

If the student wants to improve the grade, the whole course has to be done.

There will not be arranged any re-sit exam.

Recommended previous knowledge

Bachelor degree or similar in computer science. MFEL1010 Medicine for Non-Medical Students or similar.

Course materials

Research papers and reports.