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 purpose of the course is to introduce the topic of artificial intelligence (AI) in mental healthcare focused on theoretical development, ethics and practical application informed by a scientific approach.

This course will elevate your AI proficiency, preparing you to actively engage in the digital evolution of healthcare. It offers a comprehensive perspective on the healthcare shift, steered by medical necessities, and bolstered by innovative artificial intelligence solutions.

Topics covered include:

• Basic fluorescence microscopy
• Fluorescence lifetime imaging (FLIM), 2P excitation
• Fluorescence resonance energy transfer (FRET)
• Stochastic optical reconstruction microscopy (d-STORM)
• 3D-Electron microscopy, focused-ion beam (FIB) milling and scanning EM, specimen preparation and embedding.

This course will focus on behavioural, psychological, neurobiological, and neuropsychological processes underlying the acquisition of new knowledge and its subsequent consolidation and retrieval in human animals. Where possible, attempts will be made to integrate these levels in a multidisciplinary framework. Additionally, the application of learning and memory paradigms in clinical and cognitive research will be discussed. 

This course will provide students with a thorough background in the newly emergent field of social cognitive neuroscience. A broad range of social phenomena will be examined at multiple levels (1) the social level including experience and behaviors (2) the cognitive level which deals with information processing systems and (3) the neural level which deals with brain/neuronal bases of the first two levels.