Course - Clinical Decision Support - DT8119
Clinical Decision Support
Assessments and mandatory activities may be changed until September 20th.
About
About the course
Course content
Technology, theory and application of clinical decision- and process support. Content is aligned with student needs, but may range over: Representation of clinical knowledge, guidelines and recommendations; Interfaces for decision support; Search and ranking og recommendations; Extraction and machine learning for analysis of health data; Methods for authoring and validation of clinical guidelines; Evaluation, efficacy and consistency; Technology for decision support; Precision medicine.
Learning outcome
Knowledge: Understanding applications, theory, representations and limitations. Abilities: Using tools, be able to prototype simple decision support systems. Be able to specify such systems Analyse and evaluate effects and quality of such systems Competence: Understand the relationship with underlying scientific areas like knowledge engineering, information extraction, process support.
Learning methods and activities
Seminars, lectures, (programming) laboratory, field work and collaborative writing. Guest lectures and visits.
Compulsory assignments
- Paper
Recommended previous knowledge
Knowledge engineering, AI, clinical information systems and statistics.
Course materials
Research papers, books and tools. May be composed according to student needs. Greenes (ed): Clinical decision support, the road to broad adoption. Academic Press 2014.
Subject areas
- Computer and Information Science
- Applied Information and Communication Technology
- Clinical Medicine
- Computer Science
- Medical Computer Science
- Information Systems
- Biophysics and Medical Technology
- Computer Systems
- Computer Systems
- Allmennmedisin
- Bioinformatics
- Farmakologi
- Informatics
- Information Technology and Informatics
- Communication and Information Science