See you in San Diego! #ASH2024
We are happy to announce that our group will be joining the annual meeting of the American Society of Hematology in San Diego with six accepted abstracts! #1057: Synthetic Bone…
Our team has won the „Digital Laboratory Award“ by the German Society of Laboratory Medicine!
We are thrilled to announce that Moritz Middeke and Jan Eckardt received the “Digital Laboratory Award” of the German Society of Laboratory Medicine 🎉 They were honored for their research…
Inspiring HemAI Workshop with Janssen
At our recent HemAI Workshop in Dresden, a joint initiative between our working group and Janssen, we delved into the promising field of AI in hematology. The sessions were filled…
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
Clinical trials become increasingly more expensive and time-consuming. High failure rates especially in late phase trials put a substantial financial burden on healthcare systems and pharmaceutical companies. Hence, a paradigm…
AI at ASH!
Welcomed by the warm San Diego sun, we embarked on a week filled with exciting research and innovations in hematology at this year’s annual meeting of the American Society of…
Grand Rounds in New York City
We were pretty busy with invited talks in autumn! Jan was invited as a Grand Rounds speaker at the Tisch Cancer Institute at Mount Sinai Hospital in New York. The…
From Computer to Bench to Bedside
In one of our recent papers, we used an AI model to predict treatment response and overall survival in intensively treated acute myeloid leukemia (AML). The article was well received…
AI with AstraZeneca
During this year’s annual meeting of the German Society of Hematology and Oncology (DGHO2023), AstraZeneca invited Jan to speak about the future of healthcare with artificial intelligence. It was a great…
AI at MD Anderson in Madrid
Jan was invited to speak about computer vision in hematology at the 12th Meeting on Acute Leukemias hosted by MD Anderson Cancer Center Madrid. Enjoying the best tapas while brainstorming…
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…
Deep Learning Identifies Acute Myeloid Leukemia and Predicts Gene Mutation
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,…
