Predicting primary outcomes of brain tumor patients with advanced neuroimaging MRI measures.

ABSTRACT:

Background

Advanced neuroimaging measures along with clinical variables acquired during standard imaging protocols provide a rich source of information for brain tumor patient treatment and management. Machine learning analysis has had much recent success in neuroimaging applications for normal and patient populations and has potential, specifically for brain tumor patient outcome prediction. The purpose of this work was to construct, using the current patient population distribution, a high accuracy predictor for brain tumor patient outcomes of mortality and morbidity (i.e., transient and persistent language and motor deficits). The clinical value offered is a statistical tool to help guide treatment and planning as well as an investigation of the influential factors of the diseas

SUBMITTER: Vergun S 

PROVIDER: S-EPMC8722581 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature