Artificial intelligence (AI) or machine learning (ML) have advanced the possibilities to analyze and classify complex big data sets. Different technical approaches show differing usability for specific
required tasks, ranging from classic machine learning to sophisticated quantum deep learning. In medicine, the application of ML in image analysis allows systematic investigation of tissue sections. Given the current problems in immunotherapy of cancer patients, ML holds the promise to improve the stratification of tumor microenvironments and open new therapeutic avenues. In this talk, ML as technology will be presented alongside with examples for applications of ML in clinical translation from our department.
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Niels Halama is the head of the department of translational immunotherapy at the German Cancer Research Center. Alongside he is attending physician at the department of Medical Oncology at the National Center for Tumor Diseases in Heidelberg, Germany. His interests are in translational immunology, (immunological) tissue analyses and new technologies to address basic and translational scientific questions. These novel workflows and technologies ranging from new immunotherapies to machine learning approaches are being applied in translational projects with implementation in clinical trials.
Dr Halama is a medical oncologist by training, but he also worked in software development for engineering companies. Thus, his focus is not only on the development of high-throughput immunological tissue analytics and bioinfomatical approaches to analyze complex data sets, but also on the conduct of early phase clinical trials, bridging effectively the gap from bench to patients by seamlessly integrating these different fields for rapid clinical developments.
