Artificial Intelligence and mathematical Models in Research and applied Oncology and Hematology

Since there is an infinite number of mutations that cause cancer, and even more possible combinations than there are molecules in the universe (Califano, Science 2020), the question arises whether the conventional approach of cancer research in the laboratory ("trial-error-trial") ) is realistic to recognize the important cancer-related patterns. Artificial intelligence has already shown that it can learn to recognize patterns in complex data structures such as face recognition. This approach is already being used in the discovery of new antibiotics and should also drive the discovery of novel cancer drugs. The extent to which these findings will find their way into clinical cancer therapy remains to be seen. The next step is the validation of these theoretical findings "in vitro" on cancer cells, followed by animal experiments and clinical studies. The results so far are optimistic, but the path to the clinic will still pose a lot of challenges for science. Vortrag fand am 22.10.2020 beim Symposium "KI und Krebs - Erkenntnisgewinnung in der Krebsforschung durch künstliche Intelligenz" im Haus der Industrie in Wien statt.  AF Institute: https://www.af-institute.at