Artificial Intelligence in Mental Healthcare

Who is the clinician of tomorrow - man and machine? Together we explore how artificial intelligence (AI) is researched and integrated into mental healthcare, particular psychiatry, to improve tailored patient care. Throughout the course we discuss ethical implications of this ongoing paradigm shift and its consequences for mental health care. 

Credits: 3 hp

Period: 3 June 2024 - 17 June 2024

Level: First cycle

Department: Department of Clinical Neuroscience

Pace of study: Full-time

Application deadline: 15 March 2024

Study location: Flemingsberg

Language: English

Application code: KI-82003

The course provides a comprehensive interdisciplinary perspective on both opportunities and challenges of AI with a focus on clinical psychology and psychiatry. Using theory and real-world examples, students gain insight into the particular strengths and limitations of humans versus machines. Focus areas include conversational agents, suicide prediction, and applied machine learning for the purpose of improved tailored treatment, monitoring, and care. These topics are also studied from an ethical perspective. Lectures are supported by collaborative seminars on cutting-edge findings. Interactive workshops provide possibilities for both theoretical development and hands-on construction of AI-tools. 

Student performance will be assessed through group discussions, oral presentation, and written assessments.

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Specific entry requirements

A minimum of 60 credits in health care or medicine. And proficiency in English equivalent to English B/English 6.


The selection is based on academic credits (1-165). The selection results will be published at your account at the 25th of April 2024. 


The application is made through University Admissions in Sweden.


If you have citizenship within the EU/EEA, or Switzerland, you are not required to pay application or tuition fees. 

Application fee

900 SEK

Tuition fee

Total amount: 9,000 SEK
First instalment: 9,000 SEK
Payment of fees


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John Wallert

Course responsible and examinator
Department of Clinical Neuroscience
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