Universitat Internacional de Catalunya
Advanced Technologies and Artificial Intelligence Applications in Dentistry
Other languages of instruction: Catalan, Spanish
Teaching staff
Student support will be provided before and after class, as well as by email.
Introduction
Artificial Intelligence (AI) has become something omnipresent in today's society. The huge impact of this technology is already evident in highly technical fields, and it is expected to reach more and more professional sectors, with still uncertain labour-market consequences and important ethical challenges.
For this reason, UIC is committed to offering this subject to all its students. On the one hand, the goal is to provide basic knowledge about the technology; on the other, the aim is to analyse the potential impact of AI on the future labour market of each discipline, in this case Dentistry.
Pre-course requirements
There are no prerequisites for this subject.
Objectives
- Provide a solid understanding of the fundamental principles of AI.
- Explore the current and future impact of AI in several professional sectors.
- Reflect on the ethical challenges posed by the implementation of AI in each sector.
- Encourage critical thinking about the role of AI in labour-market transformation.
Competences/Learning outcomes of the degree programme
- CN03 - Identify the main technologies used and the possible applications of artificial intelligence in dental research.
Learning outcomes of the subject
- - Advanced Technology and Applications of Artificial Intelligence in Dentistry - CN03, HB02, HB04, CP04 - 1. Describe the current lines of research within your area of study. 2. Identify the latest technological advances, as well as the possible applications they may have in dental research. 3. Analyze the advantages and disadvantages of technology applied in dentistry. 4. Use tools for obtaining, storing and extracting data used in dental research. 5. Identify the applications of artificial intelligence in dental research.
Syllabus
The subject combines common content and content specialised in the master's area of knowledge.
- Introduction to Artificial Intelligence: what we mean by AI, the first decades.
- Foundations of AI: data, neural networks, supervised and unsupervised learning.
- Convergence between AI and supercomputing: the disruptive role of GPUs.
- Geopolitics of AI: value chain, technological sovereignty, geopolitical conflicts.
- General applications of AI: examples from Medicine to Art and Creativity.
- Ethics and AI: privacy, bias, and AI governance.
- Impact of AI in the corresponding area of knowledge (Dentistry).
- Real-world applications of AI in the professions associated with the area of knowledge.
- Future trends and opportunities.
Teaching and learning activities
In person
The core methodology will consist of theoretical–expository lectures. There will also be interactive seminars with case-study analysis and invited experts, as well as conferences by AI specialists. Group work may be considered to encourage collaboration and peer-learning, along with individual pre-readings on the topics to be covered in class.
Evaluation systems and criteria
In person
Assessment will be based on the following activities:
- Active participation and contribution in class discussions.
- Written assignments reflecting on the studied material.
The subject follows a continuous-assessment model, aimed at promoting the gradual learning of technical and specific content. The final grade is composed of:
- Active attendance: 40%
- Participation in class and seminars: 40%
- Individual / final assignments or final exam: 20%
This system seeks to reflect the student's commitment throughout the semester, valuing not only the knowledge acquired but also their involvement and continuous progress.
Students who do not meet ALL of the following requirements must take the final written exam, which will account for 60% of the final grade:
- Attendance of at least 80% of classes.
- Timely submission of all assignments and exercises.