On Monday May 30th, Geert Litjens (jr researcher Pathology/Radiology) received a Bas Mulder Award from Alpe Hu'Zes/KWF for his research proposal on improving treatment selection for prostate cancer patients using digital pathology and 'deep learning'. This award came with a 720000 euro grant which allows Litjens to carry out his proposed research project over the next six years. The award was handed to him during an official award ceremony at Alpe d'Huez in France during the yearly Alpe Hu'Zes event, which raises millions of euros every year for cancer research. Several teams from the Radboudumc also participated.
Within the project digitized specimens, so-called whole-slide images, of biopsied or resected prostate cancer will be analyzed with modern machine learning techniques (the same techniques that are used in for example self-driving cars and smartphone voice recognition) to extract quantitative characteristics describing the tumor and its micro-environment. The power of these new techniques lies in the fact that humans do not have to explain what these relevant characteristics are; these powerful new algorithms can directly learn this from the data.
At the end of the project these obtained quantitative characteristics will be related to patient outcome in conjunction with the regular grading protocol of the pathologist to obtain improved therapy stratification and prognosis estimation. This evaluation will be performed in a prospective study.
If you are interested, want to learn more about the project or the techniques used, you can contact Geert at email@example.com.
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