This course focuses on the application of artificial intelligence (AI) to medical imaging. It will explore the basic concepts and types of clinical diagnosis, as well as the characteristics of diagnostic tests, such as conditions, validity, effectiveness, and ROC curves. Possible input and output variables in the context of AI applied to diagnostic imaging will also be discussed. In addition, artificial intelligence, machine learning, and deep learning will be examined, and the history of AI and the reasons for its success will be explored. Finally, machine learning and its application to diagnostic imaging will be addressed.
Objectives
- Understand the basic concepts and types of clinical diagnosis.
- Learn about the characteristics of diagnostic tests, such as conditions, validity, effectiveness, and ROC curves.
- Learn about input and output variables in the context of artificial intelligence applied to diagnostic imaging.
- Examine artificial intelligence, machine learning, and deep learning, and understand their history and reasons for success.
- Understand the concept of machine learning and how it applies to diagnostic imaging.
Directed to
- Engineering graduates in any specialty
- Architecture graduates and graduates in the field of health sciences
- Any other graduates who wish to focus their careers on this specialty or simply wish to deepen their knowledge in this area and acquire the appropriate training to perform their jobs more effectively.
