Information Package / Course Catalogue
Artificial Intelligence in Nursing
Course Code: HF374
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 4
Objectives of the Course

To provide the knowledge and skills related to the use of artificial intelligence technologies in nursing practices.

Course Content

Definition and history of artificial intelligence technology, artificial intelligence techniques, types of artificial intelligence, usage areas of artificial intelligence, examples of artificial intelligence in health services-I, examples of artificial intelligence in health services-II, examples of artificial intelligence in nursing, artificial intelligence and nurse robots, roles and responsibilities of the nurses in artificial intelligence applications, artificial intelligence and ethics, comparison of artificial intelligence and human intelligence, state policies and regulations in artificial intelligence, the future of artificial intelligence

Name of Lecturer(s)
Assoc. Prof. Nihal TAŞKIRAN
Learning Outcomes
1.To understand the philosophy of nursing.
2.To analyze the relationship between the basic concepts of nursing
3.Internalization of professional values of nursing
4.Developed professional nursing consciousness to project nursing care
5.To use the nursing process in nursing care
6.To do research that will contribute to the Fundamentals of Nursing
7.To follow scientific developments are specific to the Fundamentals of Nursing
8.To analyze that accessed information are specific to the Fundamentals of Nursing
9.Evidence-based nursing care to project nursing care
10.To understand the basic philosophy of teaching Fundamentals of Nursing
11.Use appropriate teaching principles and methods of teaching Fundamentals of Nursing
12.Effective use appropriate assessment methods of teaching Fundamentals of Nursing
Recommended or Required Reading
1.Bacaksız, F. E., Yılmaz, M., Ezizi, K., & Alan, H. (2020). Sağlık Hizmetlerinde Robotları Yönetmek. Sağlık ve Hemşirelik Yönetimi Dergisi, 3(7), 458-465.
2.Aydın, Ş.E. (2017). Yapay zekâ teknolojisi (Artificial intelligence technology). Çukurova Üniversitesi İşletme ve Teknoloji Yönetimi Yüksek Lisans Programı Dönem Projesi, Adana.
3.Demirhan, A., Kılıç, Y. A., & İnan, G. (2010). Tıpta yapay zeka uygulamaları.(Artificial Intelligence Applications in Medicine. Yoğun Bakım Dergisi, 9(1), 31-41.
4.Broadbent, E., Tamagawa, R., Patience, A., Knock, B., Kerse, N., Day, K., et al. (2012). Attitudes towards health-care robots in a retirement village. Australasian Journal on Ageing, 31(2), 115-120.
5.Baloğlu, K.A., Kaplancalı, U.T., & Kılıç, S. (2019). Bakıma ihtiyaç duyan yaşlılar için yardımcı sosyal robot araştırması ve analizi (Social robot research and analysis for elderly people in need of care). Avrupa Bilim ve Teknoloji Dergisi, Özel sayı, 1-8.
6.Ersoy, N.A. (2019). Yapay zeka ve hemşirelik (Artificial intelligence and nursing). 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, pp.211-
Weekly Detailed Course Contents
Week 1 - Theoretical
Artificial intelligence definition and concepts
Week 2 - Theoretical
History of artificial intelligence
Week 3 - Theoretical
Artificial intelligence techniques and classifications-I
Week 4 - Theoretical
Artificial intelligence techniques and classifications-II
Week 5 - Theoretical
Robotic technologies
Week 6 - Theoretical
Usage areas of artificial intelligence
Week 7 - Theoretical
Artificial intelligence in health services-I
Week 8 - Theoretical
Artificial intelligence in health services-II
Week 9 - Theoretical
Artificial intelligence in nursing
Week 10 - Theoretical
Nurse robots
Week 11 - Theoretical
Artificial intelligence and ethics
Week 12 - Theoretical
Artificial intelligence and safety
Week 13 - Theoretical
State policies and regulations in artificial intelligence
Week 14 - Theoretical
The future of artificial intelligence
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory143270
Midterm Examination110010
Final Examination114014
TOTAL WORKLOAD (hours)94
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
OÇ-1
4
5
4
4
2
5
5
5
5
OÇ-2
4
5
4
4
1
5
5
5
5
OÇ-3
4
5
4
3
1
5
5
5
5
OÇ-4
5
5
4
3
1
5
5
5
5
OÇ-5
5
5
5
3
2
5
5
5
5
OÇ-6
5
5
5
3
2
5
5
5
1
5
OÇ-7
5
5
5
4
3
5
5
5
1
5
OÇ-8
5
5
5
4
3
5
5
5
1
5
OÇ-9
5
5
5
4
2
5
5
5
5
OÇ-10
5
5
5
5
2
5
5
5
5
OÇ-11
5
5
5
5
4
5
5
5
5
OÇ-12
5
5
5
5
4
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026