SEDS 535
Knowledge Discovery
Computer applications in medicine and biology, medical imaging technics, disease diagnosis with medical image processing, hospital information systems, patient tracking systems, mathematical modelling of medical information, networking in medical information systems.
Course Objectives
1. To teach the use of computer Networks in medical informatics,
2. To examine mathematical modelling of medical information,
3. To examine medical information systems,
4. To teach the application areas of processes and differential equations in medical informatics,
5. To examine the principles of hospital information systems.
Recommended or Required Reading
Introduction to medical informatics, Lecture notes, N. Baykal, E. Musluoğlu, Sas Bilişim, 2000.
Learning Outcomes
1. Gain knowledge about computer applications in medicine and biology
2. Understand application fields of the computer networks in medicine and biology
3. Understand the usage of mathematical modelling in medicine and biology
4. Learn medical imaging techniques
5. Learn mathematical modelling of the raw data which is provided by the medical imaging methods
6. Understand application fields of medical imaging
7. Understand processes and differential equations in medicine and biology
8. Understand hospital information systems
| Week | Topics |
|---|---|
| 1 | Introduction |
| 2 | Measurement and Data, Visualizing and Exploring Data |
| 3 | A Systematic Overview of Data Mining Algorithms |
| 4 | Models and Patterns |
| 5 | Score Functions for Data Mining Algorithms |
| 6 | Dimensionality Reduction |
| 7 | Descriptive Modeling I |
| 8 | Search and Optimization Methods |
| 9 | Descriptive Modeling II |
| 10 | Predictive Modeling for Classification I |
| 11 | Predictive Modeling for Classification II |
| 12 | Association Analysis I |
| 13 | Association Analysis II |
| 14 | Link Analysis |
Grading
Midterm 25%
Homework 25%
Research Presentation 20%
Final 30%
