Course Catalog 2008-2009
Basic

Basic Pori International Postgraduate Open University

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Course Catalog 2008-2009

LTT-4506 Medical Informatics Laboratory, 4 cr

CourseĀ“s person responsible

Jari Viik

Implementations

  Lecture times and places Target group recommended to
Implementation 1    


Requirements

Accepted laboratory exercises.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

Objectives

After completing the course you can apply basic and advanced processing methods for medical images and physiological signals. You understand the principles of basic statistical methods and you can analyze patient data.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Medical image processing.      
2. Digital processing and analysis of ECG.      
3. Statistical methods in patient material.     


Evaluation criteria for the course

Each laboratory report is assessed with 0-5 points. The works received 0 or 1 point require additional personal demonstration related to the essential content of the work.

Assessment scale:

Evaluation scale passed/failed will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Prerequisites

Course O/R
LTT-1806 Biomedical Engineering Laboratory Course Obligatory  
LTT-4016 Introduction to Medical Informatics Recommended  
LTT-4106 Processing of Physiological Signals Recommended  
LTT-4206 Processing of Medical Images Recommended  

Prerequisite relations (Requires logging in to POP)

Correspondence of content

Course Corresponds course  Description 
LTT-4506 Medical Informatics Laboratory, 4 cr LTT-4500 Medical Informatics Laboratory, 4 cr  

Additional information

LTT-4506 replaces the course LTT-4500. LTT-4506 is alternative with LTT-2506 Medical Electronics Laboratory.

More precise information per implementation

  Description Methods of instruction Implementation
Implementation 1   Lectures
Laboratory assignments
   
Contact teaching: 0 %
Distance learning: 0 %
Self-directed learning: 0 %  


Last modified13.08.2008
ModifierKirsi Reiman