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You will gain an overview of advanced prediction and classification tasks in medicine. You will learn methods for prognosis and diagnostics (e.g., risk scores, survival models, differential diagnosis, population stratification), specialized ML techniques (geometric deep learning methods for point clouds/networks, transformers, reinforcement learning) as well as topics on trustworthiness and clinical implementation of AI (bias, fairness, generalizability, data harmonization, evaluation). By the end you can apply the concepts in your own AI projects and assess their social and ethical implications.
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Official page in TUMonline · Details are not binding.