Artificial Intelligence Solutions in Healthcare (SVI_003)
About Study Course
Objective
To introduce students to the different types of artificial intelligence systems (machine learning algorithms and deep neural networks) and their usage in healthcare. Other goals include: 1) Understanding the importance of data in the artificial intelligence system life-cycle, starting from the the creation of the training dataset up to practical applications; 2) The most common problems associated with system training and their mitigation; 3) Ethical creation and use of artificial intelligence systems; 4) Near and far future perspectives and areas of development. At the end of the course students will be able to navigate through the terminology regarding artificial intelligence, will be capable to create an adequate training data set for an artificial intelligence system, will be capable of evaluating the results provided by an artificial intelligence system and will be able to identify the ethical issues associated with the creation and implementation of artificial intelligence systems.
Prerequisites
Experience in statistics and programming would be considered advantageous.
Learning outcomes
1.- Know different types of artificial intelligence systems.
- Recognize commonalities and differences between classical machine learning and neural network models.
- Know the importance of the data set used for training in the development of an artificial intelligence system.
- Know the different ways artificial intelligence can be implemented in healthcare.
- Recognize the ethical and legal challenges related to the development and implementation of artificial intelligence.
1.- Evaluate the adequacy of the artificial intelligence system's training data set for the intended purpose.
- Know the choice of an artificial intelligence system, according to the purpose and the available data set.
- Identify potential applications of artificial intelligence systems in healthcare.
- Identify legal challenges related to the use of artificial intelligence systems in healthcare.
1.- Manage and adapt the use of the dataset for training the artificial intelligence system.
- Create simple models of artificial intelligence systems.
- Know how to critically evaluate the results created by artificial intelligence systems.
- Create an artificial intelligence system development and survey plan.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Digital transformation in the health care sector | 2 | Master's | Required | ||
| Digital transformation in the health care sector | 2 | Master's | Required |
