Master’s Program in AI for Health
One example is the improved diagnosis of diseases. AI can also provide treatment recommendations for cancer patients and detect and prevent medication side effects. Furthermore, it can be used to identify early factors and predictors of sepsis in intensive care patients.
In this programme, we cover the fundamentals of AI and data science, including areas such as data mining, machine learning, reinforcement learning and natural language processing. We also address important aspects of ethics in AI. You will also gain basic knowledge in health, the emergence of diseases and how AI and other methods can be used to discover biological causes of illnesses.
The department have collaboration agreements within this area with the two universities:
- AMU Aix-Marseille University, France, and
- UNIPI Università di Pisa, Italy.
There is a possibility to take the second year of the programme at one of these two universities. In that case, you will deepen the parts within Health during your second year. This opportunity will be available for some students and you can apply when you have started the programme.
Changes to the selection process for autumn 2027
Please note that the selection process for autumn 2027 requires new supporting documentation. Follow the instructions under “How to apply” below.
You will find detailed course information, list of course literature, schedule and start date on the course information page at "Courses and timetables". Select semester in the drop-down menu and search by course name.
Courses and timetables
The first year provides basics in both AI and data science as well as biology and health. The second year provides in-depth knowledge in AI for health and ends with a degree project.
Year 1
1st semester
Foundations of data science 7.5 credits
Introduction to programming 7.5 credits
Biological foundations of health and disease 7.5 credits (Online course by UNIPI Università di Pisa, Italy)
Introduction to Information Security 7.5 credits
2nd semester
Data Mining 7.5 credits
Natural language processing – NLP 7.5 credits
Machine learning 7.5 credits
Health and the emergence of diseases 7.5 credits (Online course by UNIPI Università di Pisa, Italy)
Year 2
This program starts each autumn semester.
Please note that it is only possible to apply for this programme in the first admission round (mid-October to mid-January). The programme is not open for admission in the second admission round.
Find answers to the most common questions regarding application and requirements.
FAQ Master's programmes
Selection process
Changes to the selection process for autumn 2027
Please note that the selection process for autumn 2027 requires new supporting documentation.
The selection is made from the following three criteria:
- Grades of academic courses.
- Relevance of previous studies in relation to the programme.
- A motivation letter. The motivation letter is included in a mandatory application summary sheet for each programme under the section titled "Selection Questions". Follow the instructions below.
Required supporting documentation
Instructions:
- Fill out the sheet pdf, 100 kB.
- Save the sheet as “SAIHO_Application_Summary_Sheet.pdf”
- Submit the sheet together with your supporting academic documents at universityadmissions.se
For guidance on how to fill out the application summary sheet, please visit our FAQ.
FAQ – Application summary sheet
Please note: if you are applying to more than one programme, you need to fill out and submit a separate sheet for each programme.
Degree
Find the degree awarded for this programme in the syllabus, either in the right sidebar (desktop) or below (mobile device).
Please note, that you can only be awarded one bachelor’s degree, one master’s degree (60 credits) and one master’s degree (120 credits) in computer and systems sciences from our department.
Research
Research subjects at the department with relevance to the program:
Your profession after a degree from this programme may be working as a:
- Data scientist or machine learning scientist for designing, planning, implementing, and maintaining artificial intelligence and machine learning solutions against business requirements within healthcare.
- Developer of healthcare systems, electronic health record systems, decision support systems, health apps and more.
- Consultant for healthcare organisations, such as hospitals or pharmaceutical companies, as well as for insurance companies focused on healthcare.
- Researcher and developer in AI, health, data science, and more, within the academic world.
- Entrepreneur for those looking to start their own businesses.
