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Artificial Intelligence in Medical Imaging

What to expect from this program?

The main objectives of the Certificate of Advanced Studies (CAS) in Artificial Intelligence in Medical Imaging is to equip Medical Doctors (MDs) with the necessary skills to take a leading role in the AI-driven transformation of medicine. The course program was developed for medical professionals and provides them with the necessary knowledge and skills to translate medical problems to data science problems. By working on an AI project of their own, the participants will know the fundamental concepts of Artificial Intelligence and can thus judge the feasibility and adequacy of proposed AI solutions.


The program addresses MDs that are active in areas where image and video analysis are integral parts or that are interested in the application of artificial intelligence in medical imaging and diagnosis.


Compatibility between Studies and Professional Occupation
All study programs are conceptualized as extra-occupational programs that can be reconciled with the usual professional work. The study program includes a blended learning concept which means that remote e-learning will be complemented by concept lectures, peer learning and interactive discussions with experts.
Having only a limited number of in-class courses allows for large flexibility while at the same time permitting participants to profit from the experts’ expertise.


The study program consists of 6 modules, with altogether 12 days on-site courses supplemented with e-learning elements. The overall study time is approximately between 375 to 450 working hours and credited with 15 ECTS.


The Degree
A Certificate of Advanced Studies (CAS) in Artificial Intelligence in Medical Imaging is awarded by the University of Bern upon successful completion of the program.



Program Plan    

  • Mini-Symposium: Artificial Intelligence in Medical Imaging (public)
    The study program starts with a public mini-symposium in September 2019, providing an overview and current trends of Artificial Intelligence in Medical Imaging.


  • M1 Artificial Intelligence Project
    The first module introduces data sets for a concrete AI project in Medical Imaging. It teaches participants on how to use tools to prepare imaging data for analysis with Artificial Intelligence.
    After introducing basic principles and procedures for data preparation, participants will be able to take part in data collection processes as well as in the evaluation of large amounts of medical data by the use of Artificial Intelligence. Throughout the period of the CAS, participants will use different AI methods to analyze the data.


  • M2 Prerequisites for Statistics and Programming (e-learning)
    Module 2 is providing preliminary knowledge on statistics and programming necessary to tackle the following modules. Participants will acquire basics in Python programming that are relevant for data analysis.


  • M3 Fundamentals in Artificial Intelligence
    Module 3 teaches basic knowledge in AI models including mathematical concepts that are relevant for “building blocks” of neural networks. Participants will learn about basic elements of AI models including e.g. data representations, strategies for optimization and methods for the evaluation of AI models.


  • M4 Applied Artificial Intelligence in Medical Imaging

    Participants will learn about the relationship between a clinical problem and a machine learning problem as well as the trade-off between manual and automated labelling of training data for AI.
    Participants will know the properties of state-of-the-art AI models and learn how to apply and validate them in practice.


  • M5 Applications of Artificial Intelligence

    Module 5 reviews applications of AI-assisted image interpretation technologies in radiology,  neuroradiology,  and nuclear medicine.

    In order to integrate AI in the clinical workflow for improved efficacy, participants will be able to select and benchmark the required hard- and software for AI.


  • M6 Legal and Ethical Challenges
    New and emerging medical technologies and devices are regulated for safety and efficacy by competent authorities such as Swissmedics in Switzerland. In module 6, participants will be able to identify and solve legal ethical, and regulatory challenges related to the whole life cycle of AI technologies in the medical sector.


Admission Requirements
The admission requirements are those of the University of Bern. Required is a completed study program in medicine, professional experiences as a medical doctor and basic knowledge in the handling of medical image data sets. Admission “sur Dossier” by the study commission is possible.


The fee for the CAS in Artificial Intelligence in Medical Imaging is CHF 9’800.--


Additional Information
The study program starts in September 2019 and is designed for a duration of two  to three semesters. The course language is English.

In-class courses are held at the Swiss Institute for Translational and Entrepreneurial Medicine, sitem-insel, in Bern, Switzerland. Participants will be registered at the University of Bern.


Registration and Contact
Places available but limited.
Registration deadline: 31.07.2019
Phone: +41 31 664  6400


The sitem-insel School
The School for Translational Medicine and Biomedical Entrepreneurship (sitem-insel School) is jointly run by the University of Bern, sitem Center for Translational Medicine and Biomedical Entrepreneurship and the Swiss Institute for Translational and Entrepreneurial Medicine  in Bern (sitem-insel AG). The sitem-insel School’s focus is on different aspects of translational medicine covering the whole translational process, from basic research to medical applications.


The study program “Artificial Intelligence in Medical Imaging” is jointly organized with Inselspital, the Bern University Hospital. Faculty includes professionals from research and development, from industry, as well as medical practitioners.


Further Information
For further questions please contact:
Prof. Dr. Juergen Burger, Director sitem-insel School (
Dr. Pascale Anderle, deputy Director and program coordinator (
Dr. Anke Zürn, administration and communication (


All modules