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

The course is practical and aims at teaching students how to:

• Use the programming environment R and RStudio, which includes installation, how to handle errors, problem solve and access helper documents.
• Use basic concepts of programming, such as data types, logical and arithmetic operators, if else conditions, loops and functions.
• Use common R packages to perform basic statistical analysis (e.g., t-test, chi2-test, correlation) and visual presentation (e.g., boxplot, histogram and heat-map) of data in R.

The course is structured with the intent to gradually make students more autonomous in writing code. Starting by introducing a concept through a lecture, then providing formative quizzes and tasks relateed to the concept. This all leads up to a project (exam) where the student gets to combine multiple concepts into a project with the intent of solving a certain problem or displaying specific statistical tests of visual components. 

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