Glioblastoma (GBM) is the most common primary brain tumor in adults with 15 months median overall survival. The purpose of this study was to identify overall survival of GBM patients based on clinical and Visually AcceSAble Rembrandt Images (VASARI) features using machine learning. According to our results, a support vector machine (SVM) model worked better for categorical data classification. With the help of adaptive synthetic (ADASYN) oversampling, a fine Gaussian SVM model identified short overall survival at 12 and 24 months thresholds with 99.78% and 88.80% accuracies, respectively.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords