New professor: artificial intelligence will be the doctor's new supervisor, able to give feedback 24-7.

Martin Tolsgaard aims to strengthen learning in the clinic - through new technology. With his new professorship, he will use artificial intelligence to reduce medical and surgical errors - and help clinicians become even better at what they already do.

Martin Tolsgaard will be a professor with a special focus on clinical education from 1 January 2023. He will make artificial intelligence the doctor's new feedback partner.

The professorship and the associated position of chief physician are affiliated with both the Department of Pregnancy, Childbirth and Maternity at Rigshospitalet and CAMES (Copenhagen Academy for Medical Education and Simulation). The professorship is anchored in the Department of Clinical Medicine at the University of Copenhagen.

Martin G. Tolsgaard is working to introduce new technology such as artificial intelligence to support clinical learning and clinical performance. Through a collaboration with DTU (Technical University of Denmark) and the Department of Computer Science at the University of Copenhagen, Martin Tolsgaard and his research group have a special focus on developing artificial intelligence that can be used for competence assessment and feedback in clinical procedures - both for doctors in training and in the highly specialised daily life at Rigshospitalet, among others.

Martin Tolsgaard hopes that in his new five-year professorship he can contribute to the active use of artificial intelligence in clinical practice to a much greater extent than is the case today. Not least when it comes to training clinical skills and providing feedback at specialist level to both newly qualified doctors, doctors in training and experienced specialists who have been working in the field for many years.

Martin Tolsgaard explains:

- As clinicians, we work alone a lot on a daily basis, regardless of speciality, and there are often limited opportunities for supervision or feedback from experts. This may be because experts also have to see their own patients, are not on call 24/7, or because there is no time or resources for an extra person in the room when an intervention is needed. If we can develop new ways to provide feedback to and supervise both newly trained and experienced clinicians via artificial intelligence, we will be able to ensure that all doctors achieve and meet the same expert standards to a much greater extent than today.

One example of some of the research that Martin Tolsgaard's group is doing is developing automated competency assessments for procedures such as placenta tests. Here, it is important that new doctors master the procedure before they have to perform the procedure on patients.

- To train new procedures safely, we often develop simulators (manikins) - for example by 3D printing them on CAMES. Then CAMES engineers have developed an artificial intelligence algorithm that can help make competency assessments based on eye movements, hand movements and ultrasound images. This allows us to determine when a new doctor has reached the same level as a clinical expert and is therefore ready to move on to clinical training. This helps to cut out the whole 'dangerous' part of the learning curve - and thus significantly reduce the risk associated with the procedure for patients, explains Martin Tolsgaard.

The aim of the new professorship is to raise clinical education to a new level using new technologies and to put Denmark in a leading position in research in medical education and the development of sustainable, future-proof solutions.

- I hope that in the collaboration between Rigshospitalet and CAMES, we can develop and consolidate our international leadership position in research in medical education, so that Denmark becomes a pioneering country for the digital future with the use of artificial intelligence. This could be through new technology where we use large amounts of patient data to develop decision support tools based on artificial intelligence. It can also be by developing systems for systematic competence assessment of healthcare professionals - including experienced clinicians. Ultimately, the ambition is to reduce inequalities in the care you receive depending on where you are in the country and which doctor you are seen by. And hopefully we can develop algorithms and systems that are easy to use and valuable in ensuring that all patients get the best possible treatment and diagnostics," concludes Martin Tolsgaard.

Martin Tolsgaard will take up the new professorship on 1 January 2023.