Computational Hematology and Immunotherapy Workgroup

Allogeneic hematopoietic stem cell transplantation is one of the main therapies for intermediate- and high-risk patients with hematologic malignancies (e.g. acute myeloid leukemia (AML)). Although transplantation is an established treatment, there are several associated complications, which can reduce good clinical outcome. Our group uses mathematical models and machine-learning approaches to identify significant parameters of complications. The development of such models can enhance the treatment of patients according to their risk profiles which will lead to a better quality in patient care and individual therapy outcomes. Ideally, patients may be prevented from or treated for complications before they occur.