“Because of the heterogeneity of this disease, scientists haven’t found good ways of tackling it,” said Olivier Gevaert, PhD, associate professor of biomedical informatics and of data science.
Doctors and scientists also struggle with prognosis, as it can be difficult to parse which cancerous cells are driving each patient’s glioblastoma.
But Stanford Medicine scientists and their colleagues recently developed an artificial intelligence model that assesses stained images of glioblastoma tissue to predict the aggressiveness of a patient’s tumor, determine the genetic makeup of the tumor cells and evaluate whether substantial cancerous cells remain after surgery.
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