Projects that live


Explore selected simulation-based projects and initiatives that CAMES has solved, is behind - or has in the pipeline.

CAMES Robotics

Explore - and get inspired when you click through to our brand new simulation-based robotic surgery competence centre.
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We have a dedicated team of researchers and experts working with artificial intelligence to enhance clinician learning and performance.
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Cases and research projects

See current projects that CAMES is involved in - and tasks we have solved for partners in the healthcare system.
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CAMES focuses on robotics with new competence centre

CAMES Robotics is a centre of excellence for robotic surgical training and educational research - offering best practice training programmes for doctors and surgical nurses in robotics across multiple systems.

See current training and consultancy offers and be inspired by concrete cases and research projects. 


How we're using artificial intelligence to boost clinician learning and performance

CAMES AI works with artificial intelligence in medical education. AI technology is being researched and developed to support and improve learning processes, decision-making and daily work in hospitals.

See specific AI projects, find contact details - and learn more about working with AI. 

Selected projects

Discover for yourself selected cases CAMES is behind or involved in.



See a selection of projects from CAMES Research.

VR-based training in surgical treatment of fractures

In Denmark, around 30,000 surgical procedures are performed each year for fractures. There is therefore an ongoing need for training of new, competent, orthopaedic surgeons to provide this treatment.

A 2019 national needs survey, including all of the country's orthopaedic surgery departments, showed that principles of surgical treatment of fractures is the orthopaedic surgery area where the need for simulation-based technical training is greatest.

The training of surgical competence traditionally consists of self-study and surgery under supervision. In other words, doctors actually train on patients. By having the earliest part of the training take place on a simulator, doctors can learn from their mistakes and achieve sufficient surgical competence before performing real operations. In this way, patients are not exposed to unnecessary risk.

The project:

The VR BOSS project (Virtual Reality Basic Osteosynthesis Surgery Simulation) is working on the development and implementation of a VR simulator for training and competence assessment in the surgical treatment of bone fractures.

The project has established a collaboration with the world-leading orthopaedic surgery organisation AO Foundation. Through this collaboration, orthopaedic surgical education experts from around the world have defined the parameters on which users of the simulator should be assessed, as well as how each parameter should be assessed. This novel approach to simulator development ensures that development is evidence-based, that the simulator meets the requirements and expectations of the target audience - and that the entire development process is transparent from the outset.

The development of the first of a total of seven orthopaedic surgical procedures is in its final phase, after which studies will begin to determine the validity of the simulator test and the impact of the simulation training.

Check out the VR simulator:

Here you can see how the VR simulator - developed by CAMES PhD student Mads Emil Jacobsen - works when surgeons train fracture surgery.

Cooperation and support

The VR-BOSS project is supported by grants from the Toyota Foundation and the Health Fund as well as Region Zealand's Research Fund and the Næstved- Slagelse- Ringsted Hospital Research Fund.

The project is anchored as a PhD with Mads Emil Jacobsen, md, PhD student, in the lead.





AI-based training in the diagnosis of birthmark cancer

Through training using a mobile application, the project aims to make it more efficient for doctors to learn how to diagnose skin cancer. What we also call "Intelligent" learning in pattern recognition.
It currently takes more than 6 years to become proficient at telling the difference between benign and malignant skin tumours. This leads to delayed diagnosis of skin cancer and high costs for the healthcare sector due to unnecessary removal of benign tumours. The reason for the slow upskilling of doctors is probably that it is difficult for a young doctor to get visual feedback on a large number of skin tumours of different types.

We're working to improve this by giving doctors and nurses access to training in skin diagnostics via the learning app - Dermloop Learn. (See photos from the app store)

The app exposes the doctor to a huge library (20,000+ cases) of images of previous skin tumours and their diagnosis. Doctors are guided through a learning process optimised by artificial intelligence, which continuously measures the doctor's multi-dimensional competence and selects the optimal learning material based on this.

Results and effects:

As part of the research project, 76 medical students with no previous experience were trained in skin cancer diagnosis for 8 days. And they reached the same level as doctors with 3-4 years of experience. Combined with a tele-dermatology extension of the system, there is plenty of potential - in terms of economics, skills development and patient safety. For example, the research group behind the project has estimated that up to €800 million could be saved in healthcare. DKK 800 million a year if the technology were implemented nationally and used by all general practitioners, dermatologists, plastic surgeons and pathologists.


Niels Ternov, MD, Ph.d - Mail: Read bio
Martin Tolsgaard, Head of CAMES AI - Mail:
Team training in robotic surgery

The PhD project is about investigating the non-technical skills of the robotic surgical team.
The robotic surgical team differs from other health professional teams in that one of the team members - the surgeon - is physically separated from the rest of the team and the patient bed. This affects teamwork, including coordination. Among other things, the team does not have eye contact with the surgeon during the operation, who also cannot see the operating theatre, but only the video screen with the operating field.

We examine and compare how the experienced and inexperienced robotic surgical teams coordinate their work to optimize teamwork and patient safety. Team coordination has an impact on workflow and on the risk of errors during surgery. Training teamwork can reduce errors and increase patient safety

The project contributes to the development of the Capital Region's robotic surgery training, where teamwork is trained to increase patient safety in both routine and emergency situations.

The PhD students carrying out the project are: Doctor Jannie Lysgaard Poulsen, who is a PhD student at the University of Copenhagen and at the Copenhagen Academy for Medical Education and Simulation at Herlev Hospital.


Jannie Lysgaard Poulsen, PhD student and doctor - Mail: Read bio

Find your way

Virtual tour: check out our facilities for technical courses

CAMES Rigshospitalet is equipped with state-of-the-art training equipment, which is used for our technical simulation courses and training. Check it out for yourself with a virtual tour of our premises. When you get around to the different facilities, you can read more about the equipment, purpose - and course activities associated with them.

You can use the slider with the arrows to get around to the different rooms on the 4th floor and CAMES Robotics on the ground floor.