From the beginnings ...
When he took over his research professorship, Prof. Dr. Walter Swoboda founded a DigiHealth working group, from which today's institute organically emerged. For more than three years, the DigiHealth Institute has now offered young scientists the opportunity to advance their own research and build a scientific career.
We wanted to build a scientific nest for our PhD students and create a good breeding ground for interdisciplinary projects.
"I think this is very important, because the demands are constantly increasing and only with outstanding specialists who are also internationally networked will Germany be able to keep up as a science location," says Prof. Dr. Walter Sowoboda, who has headed the DigiHealth Institute since its beginnings.
... until today
This has been a success: the institute team has since tripled in size and now consists of 15 people, including eight doctoral students, almost all of whom are affiliated with the Bavarian Science Forum (BayWISS) and have excellent networks. "I appreciate working at the institute because we are a dynamic team with a broad and interdisciplinary focus - so research is done on many interesting topics and you learn something every day," explains team member Felix Holl, who is currently doing his doctorate on evaluation methods for mobile health applications.
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The institute directors
Prof. Dr. Walter Swoboda
heads the DigiHealth institute. as a physician and computer scientist, the research professor works at the interface of health (care) and digitization. prof. dr. walter Swoboda is also founder and chairman of the joint ethics committee of the Bavarian universities (GEHBa). "if there is still time for my own research in addition to my management function, I am interested in ethical issues and in topics concerning the future design of the health care system."
Priv.-Doz. Dr. Elmar Buchner
acts as deputy director of the Institute; a role that complements his overarching function in strategic research funding: "In addition to administrative tasks such as the Institute's funding, my primary concern is to establish and ensure a good academic environment at the Institute and to provide a research-oriented atmosphere. As a kind of 'integrative interface', I promote the exchange between the doctoral researchers and the professors involved at the Institute.
![Walter Swoboda Walter Swoboda](/fileadmin/_processed_/a/e/csm_Swoboda_Walter_b1322a2d0c.jpg)
Our institute in three key words? Interdisciplinary - innovative - collegial.
The research topics
Technology meets informatics meets health care: At the interfaces of this triad, which the DigiHealth team deals with, highly topical issues arise. Today, IT systems and digital technologies have already become indispensable in the health sector, and the need for innovative solutions is constantly increasing. This involves very different dimensions of digitisation, all of which contribute to increasing the quality and efficiency of health care - classic examples are networking in the health care system (telematics infrastructure), the electronic patient file (ePA) or digital health applications (DiGA). At the DigiHealth Institute, too, the focus is on essential areas of the digitalisation of health care with mobile applications, technical assistance systems and telemedicine, but that is not all: in keeping with the interdisciplinary orientation of the Institute, research is also being conducted on the spread of diseases due to invasive insect species or the social acceptance of geothermal energy, among other things. Here, the Institute is currently planning a second doctoral position to analyse not only acceptance and feasibility but also regional needs, as Priv.-Doz. Dr Elmar Buchner reports. "Geothermal energy has enormous potential – but there is a lack of openness to technology. We want to counteract this with our research."
In the areas of care, financing, ethics, AI/machine learning and health and environment, the need for research is great and will continue to grow. These are all focus areas in which we are very well positioned at the Institute.
What factors promote or hinder the progress of digitalisation in the health sector in Germany? What are the potentials for counselling, treatment and care? How must new technologies be evaluated with regard to their effects and potentials? What is the acceptance of new technologies among employees in the health sector? These are just some of the questions that the DigiHealth Institute is currently addressing and will address in the future.
In the medium term, the focus is on securing funding through research applications, explains Prof. Dr. Walter Swoboda. Here, of course, it is also a matter of keeping the nest created for the scientific staff and – keyword temporary employment contracts – securing their jobs.
In the long term, the Institute will continue to move in the area of tension between medicine/nursing and technology: "As a comparatively small institute, we will continue to offer high-quality research, taking advantage of our high flexibility. How will AI and genetic engineering change our world? These are questions we will have to face in the future. For me personally, the ethical evaluation is particularly important."
How will AI and genetic engineering change our world? These are questions we will have to face in the future.
Machine learning methods for better tumour detection
One of the current research projects at the DigiHealth Institute is the NAP project (Neuronal Network Assisted Pathology). Here, research associate Daniel Hieber is conducting research together with DigiHealth colleagues Prof. Dr Johannes Schobel and Maximilian Karthan and the Institute of Pathology and Molecular Diagnostics at Augsburg University Hospital to improve the detection of glioblastomas – malignant brain tumours with an inauspicious, i.e. unfavourable prognosis. The reason: the heterogeneity of glioblastomas, i.e. the question of how much the tumours differ in themselves, is, according to current knowledge, a decisive reason for their resistance to therapy: the more heterogeneous the glioblastoma, the more difficult it is to detect.
Because the (manual) determination of this heterogeneity is a very lengthy process – a neuropathologist would be busy with such a determination for between four and eight hours – it is, however, not part of standard diagnostics.
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So solutions are needed that standardise or at least simplify heterogeneity determination and thus potentially enable new therapeutic approaches – and this is where the NAP project comes in. The DigiHealth researchers are training machine learning models that automatically analyse tissue sections highlighted by haematoxylin-eosin (HE) staining. These HE slides are produced as standard in tumour diagnostics, so they do not represent an additional burden for clinical staff. With this method, which has an accuracy of 67%, heterogeneity determination in glioblastomas is possible within minutes instead of hours.
The Institute of Neuropathology at TUM provides the necessary image data for this. The individual image scenes of the pathological sections are each around 6.5 gigabytes in size and have a resolution of 70,000 by 40,000 pixels.
Ansprechpartner
Daniel Hieber
Research associate for machine learning and digitalization in neuropathology.
![[Translate to English:] [Translate to English:]](/fileadmin/_processed_/2/a/csm_Hieber_Daniel_e1b88ba614.jpg)