This course aims to equip students with a broad understanding of digital health, emphasizing not only technical skills but also ethical considerations and critical thinking when designing, developing, and implementing digital tools in healthcare settings. The main objective is to set the stage for digital health, in general, and to understand the impact of design, development, and use of digital tools within healthcare settings for optimization purposes, in particular. By the end of the course, the students will be able to illustrate introductory knowledge of digital health, encompassing design, development, and utilization of digital tools in healthcare settings, as demonstrated by their assignment, where the focus is to design a mobile application for a specific case as well as reflect on the ethical implications of working with artificial intelligence as an embedded part of healthcare.

The course instructor is Dr. Anna Sigridur Islind, a professor at the department of computer science at Reykjavik University. 

To register, contact: islind@ru.is

This course will cover:

• Intro to Jupyter Notebooks, IDEs
• Intro Python (loops, variables, functions)
• Core packages (Numpy, Pandas, Matplotlib, Seaborn)
• Accessing folders (shell, OS)

The following content will be covered by the practical course:

• Isolation of mitochondria
• Blue native electrophoresis to study mitochondrial protein complexes.
• Activity assays of respiratory chain complexes
• Membrane potential measurements
• Studies of mitochondrial morpholog
• Protein-protein interaction studies

The module presents a variety of fundamental models and methods from computational neuroscience. By solving daily exercises the students learn how to practically apply the acquired concepts. The course introduces the employed more
advanced mathematical tools embedded into the different topics. Further there will be a pre-course teaching the required programming skills in python.