Estimating Progression-Free Survival in Patients with Primary High-Grade Glioma Using Machine Learning.

ABSTRACT: Background/Objectives: High-grade gliomas are the most common primary malignant brain tumors in adults. These neoplasms remain predominantly incurable due to the genetic diversity within each tumor, leading to varied responses to specific drug therapies. With the advent of new targeted and immune therapies, which have demonstrated promising outcomes in clinical trials, there is a growing need for image-based techniques to enable early prediction of treatment response. This study aimed to evaluate the potential of radiomics and artificial intelligence implementation in predicting progression-free survival (PFS) in patients with highest-grade glioma (CNS WHO 4) undergoing a standard treatment plan. Methods: In this retrospective study, prediction models were developed in a coho

SUBMITTER: Kwiatkowska-Miernik A 

PROVIDER: S-EPMC11508924 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature