Talking AI in Hematology @Spotify
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…
Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles
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…
Supervised Learning predicts therapeutic success in acute myeloid leukemia
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…
Congratulations to Szymon for Defending his Excellent Master Thesis!
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…
Presenting at „Shaping the Future of Medicine“ 2022 in Leipzig
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…
Semi-supervised learning in cancer diagnostics
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 Detects Acute Promyelocytic Leukemia From Bone Marrow Smears
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…
Congratulations to Zizhe Wang for his Outstanding Diploma Thesis Defense!
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…
Supervised Machine Learning Predicts Response to Chemotherapy in Acute Myeloid Leukemia
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…
Reinforcement Learning for Precision Oncology
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…
