Information Package / Course Catalogue
Artificial Intelligence in Healthcare
Course Code: YZO267
Course Type: Area Elective
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 4
Objectives of the Course

To introduce students to the basic concepts and applications of artificial intelligence (AI) in the healthcare sector.

Course Content

Introduction and Importance of Artificial Intelligence in Healthcare, Fundamentals of Machine Learning, Data in Healthcare: Governance and Ethical Considerations, Artificial Intelligence in Medical Imaging and Diagnosis, Natural Language Processing in Healthcare Documentation The course will also examine ethical considerations, data management, and the future impact of AI in healthcare.

Name of Lecturer(s)
Ins. Ümit BULUT
Learning Outcomes
1.Understands the basic principles and algorithms of artificial intelligence in the healthcare field
2.Recognize AI applications in diagnosis, treatment planning and patient monitoring in the healthcare field
3.Evaluates the impact of AI on patient outcomes and clinical decision-making in healthcare.
4.Imagines the future developments of AI and its potential to transform the field.
5.Students become familiar with various AI tools and technologies that are revolutionizing patient care, diagnosis, treatment planning, and personalized medicine.
Recommended or Required Reading
1.Kumar, A., Ahirwal, M. K., & Londhe, N. D. (2022). Artificial Intelligence Applications for Health Care. CRC Press.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction and Importance of Artificial Intelligence in Healthcare
Week 2 - Theoretical
Fundamentals of Machine Learning
Week 3 - Theoretical
Data in Health: Governance and Ethical Considerations
Week 4 - Theoretical
Artificial Intelligence in Medical Imaging and Diagnosis
Week 5 - Theoretical
Natural Language Processing in Health Documentation
Week 6 - Theoretical
Predictive Analytics in Patient Care
Week 7 - Theoretical
Wearable Technology and Patient Monitoring
Week 8 - Theoretical
Telehealth and Artificial Intelligence
Week 9 - Theoretical
Ethical Implications of Artificial Intelligence in Healthcare
Week 10 - Theoretical
Legal Aspects and Data Privacy in AI Healthcare Solutions
Week 11 - Theoretical
Case Studies: AI Success Stories in Healthcare
Week 12 - Theoretical
The Future of Artificial Intelligence in Healthcare
Week 13 - Theoretical
Robotics and Artificial Intelligence in Healthcare
Week 14 - Theoretical
Robotics and Artificial Intelligence in Healthcare
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142256
Reading26522
Midterm Examination110111
Final Examination110111
TOTAL WORKLOAD (hours)100
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
4
4
4
4
3
3
3
4
4
4
5
5
OÇ-2
4
4
5
5
5
4
4
4
5
5
5
5
OÇ-3
4
4
4
5
5
5
5
4
4
4
5
5
OÇ-4
4
4
3
4
3
3
3
3
4
4
4
4
OÇ-5
4
5
5
4
4
4
4
4
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026