TÜRKÇE
ENGLISH
Information
| Unit | ABDİ SÜTCÜ HEALTH SERVICES VOCATIONAL SCHOOL |
| MEDICAL DATA PROCESSING TECHNICIAN PR. | |
| Code | TVZ203 |
| Name | Artificial Intelligence and Machine Learning in Healthcare |
| Term | 2026-2027 Academic Year |
| Semester | 3. Semester |
| Duration (T+A) | 2-2 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ŞULE SULTAN MENZİLETOĞLU YILDIZ |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
This course introduces the applications of artificial intelligence (AI) and machine learning (ML) in healthcare. Students will learn about the fundamental principles of AI, types of algorithms, healthcare data analysis, the use of AI in diagnostic and therapeutic support systems, ethical issues, and current best practices.
Course Content
This course introduces the applications of artificial intelligence (AI) and machine learning (ML) in healthcare. Students will learn about the fundamental principles of AI, types of algorithms, healthcare data analysis, the use of AI in diagnostic and therapeutic support systems, ethical issues, and current best practices.
Course Precondition
None
Resources
Lecture notes to be given by the instructor
Notes
Lecture notes to be given by the instructor
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Defines the concepts of artificial intelligence and machine learning. |
| LO02 | Explains the basic structures of AI and ML algorithms. |
| LO03 | Explains artificial intelligence applications used in healthcare with examples. |
| LO04 | Evaluates the analysis processes of health data with AI systems. |
| LO05 | Discusses the ethical and legal aspects of artificial intelligence in the field of healthcare. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Defines the concept of health informatics. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Explains the types and sources of health data. | |
| PLO03 | - | Analyzes the processing, storage and sharing of health data | |
| PLO04 | - | Summarizes the structure and function of health information systems. | |
| PLO05 | - | Evaluates the effects of digitalization in healthcare. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to artificial intelligence and machine learning | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 2 | History and development of artificial intelligence in healthcare | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | Basic types of machine learning (supervised, unsupervised, reinforcement) | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 4 | Examples of algorithms: Decision trees, regression, clustering | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 5 | Preparing big data and health data for AI | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 6 | AI applications in healthcare: Image analysis, diagnostic support systems | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 7 | AI with mobile health applications and smart devices | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 8 | Mid-Term Exam | Lucture Notes | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Artificial intelligence-supported treatment planning systems | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 10 | Data mining and natural language processing (NLP) | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 11 | Data privacy and security in artificial intelligence | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 12 | Ethical issues: discrimination, transparency, responsibility | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 13 | Application examples and case studies | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 14 | General evaluation and project presentations | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 15 | project presentation | Lucture Notes | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 16 | Term Exams | Lucture Notes | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Lucture Notes | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 24 | 24 |
| Final Exam | 1 | 40 | 40 |
| Total Workload (Hour) | 120 | ||
| Total Workload / 25 (h) | 4,80 | ||
| ECTS | 5 ECTS | ||