Glioblastoma Multiforme (GBM), a grade IV glioma, is the most malignant form of central nervous system tumors. Symptoms can include headaches, seizures, nausea, and sensory/cognitive problems. Due to the genetic heterogeneity and different mutations within a single tumor, this tumor is difficult to treat. Genetic mapping is one particular method used to determine the signaling pathway and the subsequent mutated gene which plays a role in GBM. Such potential mutations are targets for inhibition of GBM risk factors.

A tool for GBM treatment plan development incudes an Artificial Neural Network system since it safely assesses GBMs, unlike intracranial methods which pose a greater risk. The Artificial Neural Network system was found to posses a 80 to 85 percent accuracy rate, highlighting the tool as a key to increase survival rates for GBM. Furthermore, there is currently no model which characterizes GBM in humans completely, however, genetically modified mouse models, cell lines, stem cells, and analysis of brain slice samples help as models for GBM. Thus, future research includes the use of artificial intelligence and immunotherapies.