Stefan Posch Photo Credit: Uni Halle / Markus Scholz |
"Artificial Professor" is the nickname for a new research project at the University Hospital Leipzig and at the Martin Luther University Halle-Wittenberg (MLU). A team of doctors and bioinformatics wants to use self-learning software to significantly improve the therapy of lymphatic cancer (Hodgkin's lymphoma) in children. The second phase of the multi-year project recently began with 40,000 euros in funding from the Mitteldeutsche Kinderkrebsforschung Foundation.
Children affected by lymph gland cancer can now be cured with modern treatment methods such as chemotherapy and radiation in 95 percent of cases. However, intensive treatment in childhood often leads to late damage. Irradiation in particular increases the risk of developing a second cancer later. Long-term studies show massive over-mortality due to second diseases, such as cancer or heart diseases in adulthood.
Therefore, the primary goal of the medical profession is: only as little treatment as necessary. The data analysis developed in the project, based on artificial intelligence, is intended to help and optimize therapy for each individual patient. In the first phase, the researchers first prepared and prepared a unique data set for the big data analysis: a network of 270 child cancer clinics from 21 countries sent the data from the imaging PET examinations anonymously to Leipzig for years. The three-dimensional image series shows how well individual therapies work and how the tumor tissue develops over time.