Machine learning enhances early detection of glioma mutations

May 20 2024Karl Landsteiner University of Health Sciences Machine learning methods can quickly and accurately diagnose mutations in gliomas – primary brain tumors.

Gliomas are the most common primary brain tumors. Despite the still poor prognosis, personalized therapies can already significantly improve treatment success. However, the use of such advanced therapies is based on individual tumor data, which is not readily available for gliomas due to their location in the brain. Imaging techniques such as magnetic resonance imaging can provide such data, but their analyses are complex, demanding and time-consuming.

In the current study, the team used ML methods to analyze and interpret these data in order to obtain a result more quickly and to be able to initiate appropriate treatment steps. But how accurate are the results obtained? To assess this, the study first used data from 182 patients at University Hospital St. Pölten, whose MRI data were collected according to standardized protocols.

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