Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
INTELLIGENCE AND APPLICATIONS IN HEALTH SCIENCES SHM279 3. Semester 2 + 0 2.0 4.0

Prerequisites None

Language of Instruction Turkish
Course Level Associate's Degree
Course Type Elective
Mode of delivery
Course Coordinator
Instructors Özge ÖZDEMİR
Assistants
Goals The aim of the lecture is to teach our students,future health professionals, the importance of digital transformation and artificial intelligence and their use in health sciences and medical imaging, in the light of innovation and technological developments in the field of health.
Course Content Introduction to artificial intelligence and digital transformation in health; History of modern artificial intelligence; Essential components of digital transformation and artificial intelligence; New technology trends in health sciences; Data mining and its applications in medicine; clinical decision support systems; digital hospital; The disadvantages of artificial intelligence applications in health sciences and ethics; Blockchain technology in healthcare; Artificial intelligence reality technologies in health; Artificial intelligence and its applications in medical imaging; artificial intelligence and its applications in oncology; 5G Era in Healthcare; Main artificial intelligence applications frequently used in health sciences.
Learning Outcomes 1) Students define and know the importance of digital transformation and artificial intelligence in health.
2) Students learn about the components of technology and artificial intelligence developing in the health science.
3) Students know the applications of data mining in medicine.
4) The student knows artificial intelligence technologies in health science.
5) The student knows the drawbacks and ethical implications of artificial intelligence technologies used in health science.
6) Students know and define artificial intelligence applications used in medical imaging.
7) Students know and describe artificial intelligence applications that are frequently used in other fields of health sciences.

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction to artificial intelligence and digital transformation in health Lecture

 Homework
2. Week History of modern artificial intelligence Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
3. Week Essential components of digital transformation and artificial intelligence Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
4. Week New technology trends in health sciences Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
5. Week Data mining and its applications in medicine Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
6. Week Clinical decision support systems and digital hospital Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
7. Week The disadvantages of artificial intelligence applications in health sciences and ethics Lecture; Question Answer; Discussion

Brain Based Learning 		Homework Presentation (Including Preparation Time)
8. Week MIDTERM EXAM Question Answer
9. Week Blockchain technology in healthcare Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)
10. Week Artificial intelligence reality technologies (AR, VR, MR, XR, CR) in health Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)
11. Week Artificial intelligence and its applications in medical imaging. Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)
12. Week Artificial intelligence and its applications in oncology Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)
13. Week 5G Era in Healthcare Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)
14. Week Main artificial intelligence applications frequently used in health sciences Lecture; Question Answer; Discussion

Brain Based Learning 		Presentation (Including Preparation Time)

Sources Used in This Course
Recommended Sources
Jülide Güzin KARAGÖZ, SAĞLIKTA DİJİTAL DÖNÜŞÜM. KUTLU YAYINEVİ, İSTANBUL, 2018.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3DK4DK5DK6DK7
PY155555343

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
. 14 2
Course Duration (Total weeks*Hours per week) 14 2
Work Hour outside Classroom (Preparation, strengthening) 14 3
Homework 2 3
Midterm Exam 1 1
Time to prepare for Midterm Exam 1 5
Final Exam 1 1
Time to prepare for Final Exam 1 10
1 1
1 1
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload