Jan has recently been invited to the Onko 3.0 Podcast hosted by Dr. Friedrich Overkamp. Friedrich and Jan talked about how the digitization of medicine and integration of artificial intelligence…
The recent years have brought a lot of advancements in understanding leukemia biology due to comprehensive studies investigating molecular alterations. Risk stratification, however, is still largely restricted to simplistic decision-making…
Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia (AML) while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk…
Szymon Darius Chrost finished his Master thesis in bioinformatics with an excellent result! Szymon explored possibilities of investigating sparse patient data. In a large cohort of patients with acute myeloid…
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…
Deep learning usually thrives on large data sets, which makes the training of classifiers in rare cancer entities rather complicated. Acute promyelocytic leukemia (APL) is a rare subform of acute…
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…