Prediction of lower-grade glioma molecular subtypes using deep learning

ConclusionsA deep learning model was developed to diagnose the molecular subtype preoperatively based on multi-modality data in order to predict the 3-group classification directly. Cross-validation showed that the proposed model had an overall accuracy of 68.7% for the test dataset. This is the first model to double the expected value for a 3-group classification problem, when predicting the LGG molecular subtype.
Source: Journal of Neuro-Oncology - Category: Cancer & Oncology Source Type: research