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Information
| Code | DEN469 |
| Name | Artificial Intelligence in Dentistry |
| Term | 2024-2025 Academic Year |
| Semester | 8. Semester |
| Duration (T+A) | 2-0 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 2 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Öğr. Gör.Dr. ERKAN TİYEKLİ |
| Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to provide the acquisition of knowledge and skills regarding the use of Artificial Intelligence technologies in dental practices.
Course Content
In this course; Artificial Intelligence and Dentistry, Basic Artificial Intelligence Techniques and Algorithms, Artificial Intelligence Applications in Dentistry, Deep Learning and Artificial Neural Networks, Artificial Intelligence in Dentistry and Treatment Planning, Artificial Intelligence-Supported Dental Devices are included. Ethical and Legal Issues: Use of Artificial Intelligence in Dentistry Current Research and Applications
Course Precondition
none
Resources
Artificial Intelligence in Dentistry: Tools and Techniques, Introduction to Artificial Intelligence" by Wolfgang Ertel, Machine Learning Yearning" by Andrew Ng, Operations Research APPLICATIONS AND ALGORITHMS FOURTH EDITION Wayne L. Winston
Notes
Matlab, Mikrosoft Excel program
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains how artificial intelligence technologies can be used in dental applications. |
| LO02 | Defines basic artificial intelligence techniques and algorithms, and evaluate their applications in dentistry. |
| LO03 | Describes advanced artificial intelligence topics such as deep learning and artificial neural networks, and discuss how they can be integrated into dental applications. |
| LO04 | Analyzes the use of artificial intelligence-supported dental devices and assess their advantages and disadvantages. |
| LO05 | Examines the ethical and legal aspects of artificial intelligence use in dentistry, discussing the safe and ethical use of these technologies. |
| LO06 | Follows current research and applications, and anticipate the future role of artificial intelligence technologies in dentistry. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | As a dentist, identifies the fundamental and current knowledge required in clinical and health sciences relevant to the profession. | 1 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Explains the normal structure, function, development, and interactions of oral, dental, and maxillofacial formations throughout all stages of human life. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Lists the essential preventive dentistry methods meticulously aimed at preventing diseases related to the oral, dental, and maxillofacial system. | |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Associates the differential diagnoses of oral, dental, and maxillofacial diseases with systemic diseases, and manages referral and/or treatment processes when necessary. | 2 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Adopts a holistic approach to patient care, planning collaborative processes with colleagues and experts in the field. | 1 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Defines first aid and basic life support in dental emergencies requiring medical intervention, lists the necessary intervention steps, and plans the related process. | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Lists methods for protecting and preventing oral and dental health directed at individuals, families, and communities; participates in related activities as an individual or team member; and conducts consulting and supervision. | |
| PLO08 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Facilitates the participation of subordinates in developmental and educational activities and manages these activities when necessary. | |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Accesses professional knowledge and analyzes it using critical thinking skills; identifies learning needs and resources related to the practice of medicine. | 2 |
| PLO10 | Yetkinlikler - Öğrenme Yetkinliği | Develops a positive attitude and behavior towards lifelong learning, and embraces the universal conditions required by the medical profession. | 1 |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Effectively communicates with patients and their families, colleagues, and other segments of the community. | |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Organizes and implements projects and activities for the social environment in which they live, with a sense of social responsibility. | 1 |
| PLO13 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Utilizes medical informatics and communication technologies, along with computer software, at the level required by their field. | 3 |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Follows developments and communicates with colleagues in their field using a foreign language at a minimum of B1 general level according to the Common European Framework of Reference for Languages. | |
| PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Defines basic health legislation and regulations concerning individual rights and responsibilities, as well as ethical guidelines. | 1 |
| PLO16 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Exhibits sensitivity and takes responsibility in matters of individual and public health, environmental protection, and occupational safety. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Concept and history of artificial intelligence | Examining sources | Öğretim Yöntemleri: Anlatım, Tartışma, Soru-Cevap |
| 2 | Artificial intelligence techniques and algorithms | Presentation, material preparation | Öğretim Yöntemleri: Tartışma, Anlatım, Alıştırma ve Uygulama, Gösterip Yaptırma, Soru-Cevap |
| 3 | Examples of artificial intelligence use in dentistry 1 | Presentation, material preparation | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama, Gösterip Yaptırma, Gösteri |
| 4 | Examples of artificial intelligence use in dentistry 2 | Examining sources, Presentation, material preparation | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösteri, Gösterip Yaptırma, Tartışma |
| 5 | Introduction to deep learning and artificial neural networks | Examining sources, Presentation, material preparation, software installation | Öğretim Yöntemleri: Anlatım, Gösteri |
| 6 | Applications of deep learning in dentistry | Examining sources | Öğretim Yöntemleri: Anlatım, Gösteri, Gösterip Yaptırma |
| 7 | Introduction to artificial intelligence-supported dental devices, Use of artificial intelligence-supported devices in dentistry | Examining sources, Presentation, software installation | Öğretim Yöntemleri: Tartışma, Anlatım, Alıştırma ve Uygulama, Gösteri, Gösterip Yaptırma |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
|
| 9 | Ethical and legal aspects of artificial intelligence use | Examining sources, Presentation | Öğretim Yöntemleri: Tartışma, Anlatım |
| 10 | Security and ethical issues of artificial intelligence use in dentistry | Examining sources, Presentation | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Current research on artificial intelligence use in dentistry | Examining sources, Presentation | Öğretim Yöntemleri: Anlatım, Tartışma |
| 12 | Case studies and future trends | Examining sources, Presentation | Öğretim Yöntemleri: Anlatım, Gösteri |
| 13 | Project presentations and evaluation 1 | Examining sources | Öğretim Yöntemleri: Gösterip Yaptırma |
| 14 | Project presentations and evaluation 2 | Examining sources | Öğretim Yöntemleri: Gösterip Yaptırma |
| 15 | Project presentations and evaluation 3 | Examining sources | Öğretim Yöntemleri: Gösterip Yaptırma |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev, Yazılı Sınav |
|
| 17 | Term Exams 2 | Ölçme Yöntemleri: Ödev, Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 4 | 5 | 20 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 3 | 5 | 15 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 1 | 1 |
| Final Exam | 1 | 1 | 1 |
| Total Workload (Hour) | 65 | ||
| Total Workload / 25 (h) | 2,60 | ||
| ECTS | 3 ECTS | ||