| Course Type | Elective Course |
|---|
| Course Level | Master's Degree Without Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 8 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- Explain the basic concepts about the role and operation of computer systems in health information technologies
- Will be able to explain the basics of artificial intelligence
systems used in health information technologies and the concepts of functioning mechanisms
- Evaluate the performance of systems containing artificial intelligence
- Can create systems containing artificial intelligence at a
basic level by making applications in the creation of systems containing artificial intelligence
- Can explain basic concepts such as data, information,database, and query
- Explain the variables in the decision-making process and
the basic concepts of multi-criteria decision-making mechanisms in health management activities
- By following the developments about health information
technologies, gain the ability to transfer newly learned information and methods
|
| Mode of Delivery | E-Learning |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | There are no lessons related with the suggested lesson. |
|---|
| Course Description | Within the scope of this course; Information on the basics of today's computer technologies, the basics of artificial intelligence-based decision support systems and working mechanisms that can be used frequently in the field of health management, the basics of database management, which is also the basis of health management applications, the decision-making processes in the field of health management and the basics of multi-criteria decision-making mechanisms are given.Various applications of related topics are also supported by practical information in the laboratory environment. In addition, students are encouraged to research with homework and projects in order to follow up-to-date methods and mechanisms in related topics. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Computer technologies in healthcare |
|
2nd Week |
Fundamentals of artificial intelligence and decision support systems |
|
3rd Week |
Fundamentals of artificial intelligence and decision support systems |
|
4th Week |
Artificial intelligence approaches |
|
5th Week |
Artificial intelligence laboratory applications |
|
6th Week |
Database management |
|
7th Week |
Database management |
|
8th Week |
Multi-criteria decision making |
|
9th Week |
Multi-criteria decision making |
|
10th Week |
Fuzzy logic and multi-criteria decision making |
|
11th Week |
Fuzzy logic and multi-criteria decision making |
|
12th Week |
Laboratory applications |
|
13th Week |
Laboratory applications |
|
14th Week |
Project presentations and discussion |
|
15th Week |
Project presentations and discussion |
|
| Recommended or Required Reading | Handbook of Medical Informatics, by Mark A. Musen (Author), J.van Bemmel (Editor), 2002, Elsevier
Machine Learning For Absolute Beginners a Step by Step guide: Algorithms For Supervised and Unsupervised Learning with Real World Applications, by William Sullivan (Author), Raymond Kazuya (Publisher), 2017
Heaton, J. (2018). Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning: The MIT Press, 2016, 800 pp, ISBN: 0262035618.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Presentation
- Questions/Answers
- Case Study
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Project |
1 |
20 |
| Total(%) |
|
20 |
| Contribution of In-term Studies to Overall Grade(%) |
|
20 |
| Contribution of Final Examination to Overall Grade(%) |
|
80 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
|
|
|
| Preparation for Quiz |
|
|
|
| Individual or group work |
15 |
7 |
105 |
| Preparation for Final exam |
1 |
30 |
30 |
| Course hours |
15 |
3 |
45 |
| Preparation for Midterm exam |
|
|
|
| Laboratory (including preparation) |
|
|
|
| Final exam |
|
|
|
| Homework |
0 |
0 |
0 |
| Project |
1 |
45 |
45 |
| Total Work Load | 225 |
| Total Work Load / 30 (h) | 7.5 |
| ECTS Credit of the Course | 8 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
