In its Strategy 2030, the Faculty of Medicine prioritizes digitalization. Why?
Claudio Bassetti: The university has earmarked digitalization and artificial intelligence as a priority. For the Faculty of Medicine, this is even more relevant because medicine is highly influenced by digitalization. There are so many areas that are now changing – from patient care in acute and in chronic diseases, to the planning and execution of complex surgical interventions and the electronic patient record, to teaching, research and even administrative aspects in healthcare. All of these areas are being accelerated by digitalization.
The founding of the Center for Artificial Intelligence in Medicine CAIM at the Faculty of Medicine as a specialized center for research, development, and teaching in AI applications for healthcare is a clear statement of our intention to shape and promote this development.
How is medicine being transformed by digitalization?
The Corona pandemic has made us more aware of the importance of digitalization in medicine: We need to make even greater use of digital opportunities, for example by enabling teleconsultations, i.e the provision of medical care without physical presence.
Telemonitoring was also very strongly promoted by Corona, the possibility of accompanying patients in the individual manifestation of their illness. This can be the evaluation of medical imaging at a distance, or include measurements of heart rhythm, temperature, breathing and oxygen saturation, but also sleep disturbances. Here we have learned through the pandemic how we can detect deteriorations early on, for example, when people who are ill are still at home and not yet in hospital.
In addition, a large proportion of medical teaching is now taking place via digital media - also spurred by the pandemic. We are seeing that some educational topics can perhaps be conveyed better in this way than in a classic lecture hall setting.
Where do you see the role of AI in this transformation?
Digitalization also means being able to integrate and assess a lot of data. Here, artificial intelligence can help aggregate large data volumes from different sources such as laboratory data, medical imaging, genetic analysis, tissue samples from biobanks, etc. and analyze them with regard to several variables. This is important in precision medicine to offer patients the best individual therapy.
Increasingly, we want to consider all this data together to better understand health and disease. And for this compilation of multi-source data (also referred to as Big Data), we need new analytical approaches, commonly summarized as Artificial Intelligence.
Where can AI-based technologies improve patient care?
Let me give you an example from my field, neurology, which is particularly topical right now: We recently inaugurated NeuroTec, a platform to research and develop novel, flexible and cost-efficient technologies to improve diagnostics, monitoring and therapy of neurological diseases. We are working especially in the areas of motor function (Parkinson's disease, epilepsy), sleep disorders and cognition (dementia, Alzheimer's disease). The goal is to be able to monitor patients at home over a longer time, e.g. by measuring their vital data with wearables (sensors worn on the body) or nearables (non-invasive sensors installed in the household).
NeuroTec has been deliberately created at the interface of medicine, digitalization, and AI: We want to live and actively shape this transformation. For this, we need digitalization and data processing methods such as artificial intelligence. That is why we have hired a professor Prof. Athina Tzovara, as part of an interfaculty research collaboration who will work on these AI aspects.
How important is interdisciplinarity in this context?
Very important indeed! We need physicians to understand the disease, engineers to develop nearables and exploit them, physicists, mathematicians, IT specialists and industrial partners.
In Bern, we are very well positioned in this respect: One of our flagships at the university and the university hospital is translationality, i.e. the transfer of research results into practice. One of the reasons why we are strong in this area is that our bioengineers work in a very practice-oriented way thanks to their direct integration into the medical faculty and their good relationships with the Bern MedTech industry. This puts us in a very good position to take a big step towards improving patient care.
Do you also see caveats in the use of digitalization and AI in medicine?
I firmly believe that despite using all these methods, we must not displace patients from the center of care. Corona has taught us that personal interaction, regular contact and physical proximity are so important. In medicine, we cannot and do not want to completely replace this human interaction with digitalization.
Then, of course, data confidentiality is crucial. The Insel Gruppe has taken the necessary protective measures as part of its digitalization process to securely enable increased data evaluation through AI. These are two aspects that we must remain aware of.
What potential arises for the Bern Medical Hub and how will the university exploit it?
On the one hand, we are seizing the opportunity to participate in this important transformation in close interaction with society, politics, and industry. On the other hand, this transformation enables us to attract talented researchers. By creating and filling several professorships associated with biomedicine, digitalization and AI, the university has made a clear commitment to invest in this area.
Bern, as a university with a holistic approach, is also committed to increasing interfaculty collaboration in this area. The Faculty of Medicine has therefore launched several joint projects with the Faculty of Science. And, of course, close cooperation with the University Hospital is essential.
Such collaborations across disciplinary boundaries are crucial to success. After all, innovation arises when people look beyond their own field of expertise. Corona has shown us: It is not science alone, but the alliance with politics – of scientific expertise with practical decision-making power – that is needed to solve societal challenges.