Information Package
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Program of Audiology

ODYO422

ARTIFICIAL INTELLIGENCE IN HEALTH SCIENCES

Course Code
ODYO422
Semester
-
Theory+Practice
2 + 0
ECTS
3
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS3
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Understand the basic principles and algorithms of artificial intelligence related to healthcare.
  2. Learn to apply machine learning and deep learning techniques to health data.
  3. Evaluate the benefits and limitations of implementing AI solutions in the health sciences field.
  4. Gain the ability to develop health data ecosystems and data management strategies.
  5. ecognize AI applications in diagnosis, treatment planning, and patient monitoring in Audiology.
  6. Analyze how generative AI technologies can be used in the field of health sciences.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme Components
Course DescriptionThis course aims to teach Artificial Intelligence (AI) tools and technologies in the field of health sciences. Students will study the AI principles and algorithms that revolutionize patient care, diagnosis, treatment planning, and personalized medicine. The course also covers ethical considerations, data management, and the future impact of AI in the healthcare sector.
Course Contents
WEEK TOPICS
1st Week 1. Week Introduction to Artificial Intelligence: Definition, History, and Role in Health Sciences
2nd Week 2. Week Fundamentals of Machine Learning (ML): Supervised/Unsupervised Learning, Algorithms
3rd Week 3. Week Deep Learning (DL) and Neural Network Architectures
4th Week 4. Week Health Data Ecosystems: Data Types, Data Management, and Preprocessing Methods
5th Week 5. Week Image Processing and AI: Analysis of Medical Imaging Data (MRI, CT, X-Ray)
6th Week 6. Week Natural Language Processing (NLP) and AI: Analysis of Electronic Health Records (EHR)
7th Week 7. Week AI-Supported Applications for Diagnosis and Early Diagnosis
8th Week 8. Week AI-Supported Treatment Planning and Personalized Medicine
9th Week 9. Week Midterm Exam
10th Week 10. Week Use of AI in Audiology (Case Studies)
11th Week 11. Week Generative AI Technologies in Healthcare and Application Areas
12th Week 12. Week AI Ethical Principles and Legal Dimensions: Confidentiality, Bias, and Responsibility
13th Week 13. Week Evaluation of Benefits and Limitations of AI Applications
14th Week 14. Week The Future of AI and its Potential to Transform the Healthcare Field
15th Week 15. Week General Review / Project Presentations
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
  • Questions/Answers
  • Problem Solving
  • Practice
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 1 10
Total(%) 40
Contribution of In-term Studies to Overall Grade(%) 40
Contribution of Final Examination to Overall Grade(%) 60
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam
Preparation for Quiz
Individual or group work
Preparation for Final exam
Course hours
Preparation for Midterm exam
Laboratory (including preparation)
Final exam
Homework
Total Work Load0
Total Work Load / 30 (h)0
ECTS Credit of the Course3
Language of InstructionTurkish
Work Placement(s)No

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