Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
3BYM229Artificial Intelligence in Health3+0+03416.12.2025

 
Course Details
Language of Instruction Turkish
Level of Course Unit Associate Degree
Department / Program Biomedical Device Technology
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course “The aim of this course is to introduce students to the applications of artificial intelligence in healthcare from both conceptual and technical perspectives, to enable them to understand its integration with medical devices and health informatics systems, to provide them with fundamental knowledge, analytical and practical skills in this field, and to enhance their research and scientific communication competencies through individual presentation projects.
Course Content This subject provides students with an understanding of the fundamental concepts of artificial intelligence in healthcare, covering machine learning and deep learning methods, clinical applications, data management, digital hospital systems, and ethical and legal considerations, while fostering both theoretical knowledge and practical awareness.
Course Methods and Techniques Online lectures and presentations
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Instructor Ömer Şahin Şimşek
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources "Yapay Zeka ve Makine Öğrenmesi: Sağlık Uygulamaları" – Fırat Taha Mansuroğlu
"Makine Öğrenmesi ve Derin Öğrenme" – Özge Erkin, Ahmet Emir Dirik
Course Notes 1. Gedik, M. A. (2021). Artificial Intelligence in Healthcare and Its Applications. Akademisyen Kitabevi.
2. Doğan, K., & Sivri, S. (Eds.). (2020). Artificial Intelligence in Health Sciences. Nobel Kitabevi.
3. Seyhan, F., & Korkmaz, S. (2024). Artificial Intelligence and Digital Hospitals in Healthcare. Siyasal Kitabevi.
Assignments Her öğrenci için farklı konularda ödev tanımlanır. Öğrencinin ödev konusunda araştırma yaparak sunum yapması beklenir.

Course Category
Mathematics and Basic Sciences %25
Engineering %0
Engineering Design %25
Social Sciences %0
Education %0
Science %0
Health %25
Field %25

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 30
Assignment 1 % 20
Final examination 1 % 50
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 1 14
Assignments 1 10 10
Presentation 1 10 10
Mid-terms 1 15 15
Final examination 1 20 20
Total Work Load   Number of ECTS Credits 4 111

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Explains the fundamental concepts of artificial intelligence, machine learning, deep learning, and clinical decision support systems.
2 Defines the management, analysis, and digital communication standards (e.g., HL7, DICOM) of healthcare data.
3 Describes the functions and contributions of wearable devices and Internet of Things (IoT) systems in healthcare applications.
4 Illustrates the applications of artificial intelligence technologies in various medical fields (such as radiology, surgery, physiotherapy, and cardiology).
5 Analyzes the ethical, privacy, and legal dimensions of artificial intelligence applications in healthcare; evaluates current trends in this field; and demonstrates the ability to conduct independent research on healthcare-related artificial intelligence.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Artificial Intelligence Concepts and Historical Development
2 Machine Learning and Deep Learning
3 Artificial Neural Networks and Clinical Decision Support Systems
4 Healthcare Data and Data Management
5 Wearable Devices and IoT
6 AI Applications in Radiology
7 AI Applications in Surgery
8 AI Applications in Physical Therapy and Rehabilitation
9 AI Applications in Orthopedics and Cardiology
10 AI Applications in Other Healthcare Fields
11 Digital Transformation in Healthcare
12 Digital Hospital
13 AI in Healthcare: Ethical, Privacy and Legal Aspects
14 Future Trends in AI in Healthcare

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 3 3 3 4 3 5 5 5 3 1 5
C1 3 3 3 4 3 5 5 5 3 1 5
C2 3 3 3 4 3 5 5 5 3 1 5
C3 3 3 3 4 3 5 5 5 3 1 5
C4 3 3 3 4 3 5 5 5 3 1 5
C5 3 3 3 4 3 5 5 5 3 1 5

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  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=237671&curProgID=78&lang=en