Introduction to Digital Medicine

Undergraduate course

Course description

Objectives and Content

The goal is to give an overview of the field of medical data science with an emphasis on both the promises and challenges of developing and using digital technology in healthcare, during the entire human lifespan - from cradle to grave.

Content

Digitalisation is affecting every spectrum of life including medicine. For example, as remote monitoring is becoming more and more feasible, it is reshaping fundamentally how medical services are organised.

Despite its promise to save costs and increase efficiency, the progress is slow because of the requirements for new competence at every level in the health sector.

The course will enable students to develop skills and competence to understand the newly emerging field of medical data science. The course aims to give students with diverse backgrounds and interests a foundation on which they can contribute to healthcare digitalisation through research and innovation.

Learning Outcomes

Upon completion of the course, students should achieve the following learning outcomes in terms of knowledge, skills, and general competence:

Knowledge

The student can

  • Explain the field of medical data science and how it helps towards preventive, precise and personalised (P3) healthcare.
  • Understand the basic elements of:

    1. The fundamentals of human cell biology including genetics
    2. Medical and clinical data, including registry data and health data from wearable devices.
  • Recognise the ethical issues and biases associated with digitalization of health data.

Skills

The student has

  • Awareness about different forms of medical data (genomics, imaging, registries, health records and wearable devices) and ethical issues and biases associated with them.
  • Hands-on experience on dealing with real-life medical data analysis to understand both opportunities and challenges.

General competence

The student can

  • Describe state-of-art of digitalisation of health care
  • Communicate and collaborate in interdisciplinary projects in the field of medical data science

ECTS Credits

2,5 ECTS

Level of Study

Undergraduate course

Semester of Instruction

Autumn, spring

Place of Instruction

The courses are conducted online through UiB's learning platform, Mitt UiB.
Required Previous Knowledge
None
Recommended Previous Knowledge
None
Credit Reduction due to Course Overlap
DIGI116 - 2,5 ETCs
Access to the Course
Continuing education. Available to students who have been accepted into the course via UiB Videre.
Teaching and learning methods

The teaching methods are organized as online teaching with digital learning resources.

  • We use digital modules at Mitt UiB.
  • An optional in-person session will be held on UiB's campus. Attendance is not required; it is simply an additional opportunity.
Compulsory Assignments and Attendance
None
Forms of Assessment
  • To pass, all modules must be completed and approved.
  • All modules must be completed in the same semester.
  • The student has to complete all modules in before the deadline.
Grading Scale
Pass / fail
Assessment Semester
Assessment is offered both in autumn and spring.
Reading List
The reading list will be available within July 1st for the autumn semester and December 1st for the spring semester.
Course Evaluation
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.
Course Coordinator
Course Administrator