Midwifery
Course Details
KTO KARATAY UNIVERSITY
Faculty of Health Sciences
Programme of Midwifery
Course Details
Faculty of Health Sciences
Programme of Midwifery
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 2281076 | Artificial Intelligence Applications in Healthcare | 2025 | Spring | 8 | 2+0+0 | 5 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Assoc. Prof. Hediye KARAKOÇ |
| Instructor Assistant(s) | - |
Course Content
This course introduces the applications of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare. Students will acquire knowledge of the fundamental principles of AI, different types of AI algorithms, healthcare data analysis, the use of AI in diagnostic and treatment decision-support systems, ethical considerations, and current applications of AI in healthcare.
Objectives of the Course
This course introduces the applications of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare. Students gain knowledge of the fundamental principles of AI, types of algorithms, healthcare data analysis, the use of AI in diagnostic and clinical decision support systems, ethical considerations, and current applications in healthcare.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | X |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P10 | It monitors, develops and uses the developments in science and technology necessary for midwifery practices. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Scans and reports on scientific developments on issues related to midwifery science. | P.10.1 | 1 |
| O2 | Monitors, develops and uses developments in technology related to midwifery science. | P.10.2 | 1 |
| O3 | Understands the importance of health literacy in fields related to midwifery science. | P.10.3 | 1 |
| O4 | She knows what needs to be done about media entrepreneurship during her student years. | P.10.6 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to Artificial Intelligence and Fundamental Concepts |
| 2 | Introduction to Machine Learning and Deep Learning |
| 3 | Overview of Artificial Intelligence in Health Informatics |
| 4 | Collection and Preparation of Healthcare Data |
| 5 | Classification Algorithms and Their Applications |
| 6 | Regression Algorithms for Healthcare Data Analysis |
| 7 | Image Recognition Systems (Radiology Examples) |
| 8 | Midterm Exam |
| 9 | Natural Language Processing (NLP) and Patient Records |
| 10 | Clinical Decision Support Systems |
| 11 | Ethical and Legal Aspects of Artificial Intelligence Applications |
| 12 | Basic Artificial Intelligence Project Planning |
| 13 | Case Study: Patient Risk Classification Model |
| 14 | End-of-Term Review and Project Presentations |
| 15 | Project Presentations |
Textbook or Material
| Resources | Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. (2022). AI in health and medicine. Nature Medicine, 28(1), 31–38. https://doi.org/10.1038/s41591-021-01614-0 |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 50 (%) |
| Final Exam | 1 | 50 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 2 | 28 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 24 | 24 |
| Quiz | 0 | 0 | 0 |
| Homework | 1 | 24 | 24 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 24 | 24 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 142 | ||
| Total Work Load / 30 | 4,73 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P10 |
|---|---|---|
| O1 | Scans and reports on scientific developments on issues related to midwifery science. | - |
| O2 | Monitors, develops and uses developments in technology related to midwifery science. | - |
| O3 | Understands the importance of health literacy in fields related to midwifery science. | - |
| O4 | She knows what needs to be done about media entrepreneurship during her student years. | - |