Medical Machine Learning (MML)

The research group Medical Machine Learning works on developing and deploying cutting-edge machine learning methods with the goal of making a meaningful difference for patients, doctors, and hospital staff. To this end, and in collaboration with a digital-forward clinic administration, we continue to build on a SMART hospital information structure that provides access to real-world medical data. Strong funding and state-of-the-art equipment support this effort. One focus of our group lies in the exploration of unsupervised learning paradigms for recognition of oncologically relevant patterns in large and complex data.

In medical research a common approach is from bench to beside – use insights gained in laboratory experiments for new ways to treat patients. In an analogous approach, we aim at bringing our algorithms to the point-of-care, i.e. translating them into clinical practice.

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Prof. Dr. Dr. Jens Kleesiek