Christian Kobrow

I did my bachelor and master thesis at the Department of Physics at the University Heidelberg. During my study, I focused manly on computational and environmental physics, but was also in touch with medical physics. After my master thesis, which was about investigating the influence of parasites on evolution in a simulated ecosystem, I saw the opportunity to dive into the field of machine learning and cancer research and in 2021 I started my journey in the medical field. In my position as PhD student at the Department of Applied Tumor Biology of the University Hospital Heidelberg, I am currently working on two main projects.

My first project, embedded in a larger initiative, Clinic 5.1, aims to combine all medical relevant data of a patient into one digital twin. With the help of machine learning, these data are analyzed all together to improve decision-making during treatment of prostate cancer. My second project is focusing on the computational approaches for detection of cancer caused by Lynch syndrome. For that, machine learning is used to analyze histological whole slide images and find traits specific for Lynch syndrome.