Machine learning for better neurosurgical decisions in patients with glioblastoma
The most common brain tumor - glioblastoma - is a rare cancer but invariably fatal, despite surgery and chemoradiotherapy. Prolongation of patient survival and persistence of quality of life critically depend on decisions by neurosurgeons. The aim of this study is to improve these decisions in new patients by digital support systems based on patient characteristics and standard brain scans that predict decisions from experts, the tumor's growth speed, the location of tumor recurrence and the patient’s survival time. For these predictions we will combine datasets with large numbers of patients and scans in a collaboration of medical experts and machine learning experts. This should enable decision support systems to distribute expert knowledge for better neurosurgical decisions in patients with glioblastoma.
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