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Dr. Jan Eckardt presenting our work about the application of #AI in the field of #cytomorphology at this years „Shaping the Future of Medicine“ event #STFOM2022 on November 11th in…

A huge problem in clinical AI is the availability of labeled data for model training. The majority of recently introduced machine learning models in healthcare use supervised learning which requires…

For his diploma thesis, engineer Zizhe Wang developed a deep learning framework that uses state-of-the-art generative adversarial networks to generate medical images of bone marrow smears. Generative Modeling with adversarial…

Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk is…

When it comes to artificial intelligence in medicine, supervised and unsupervised learning get most of the attention. They are used, for example, to detect cancer in medical images, group patients…

Acute myeloid leukemia is the most common form of rapidly progressing blood cancer in Germany. If left untreated, it inevitably leads to death, and even with the most modern therapies,…