Medical Data Science

The course will run as normal autumn 2024

Objectives:

The course 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. This course aims to take the students through the impact of digitalisation of healthcare through all stages of human life - from cradle to death. The course will enable students to develop skills and competence to understand the newly emerging field of medical data science. The course is aimed to give students with diverse backgrounds and interests a foundation on which they can contribute to healthcare digitalisation through research and innovation.

Learning Outcomes

At the end of the course, the student will have the following learning outcome defined in 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.

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

At the end of the course, the student will have the following learning outcome defined in 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.

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

2,5 ects