Developing a deep learning model to predict epilepsy recurrence in patients with focal cortical dysplasia type III.

ABSTRACT:

Background

A sizable number of patients with focal cortical dysplasia (FCD) type III-related refractory epilepsy continue to experience seizures postsurgically. Deep learning models can automatically assess complex medical image characteristics and predict prognosis with higher efficiency. This study sought to determine whether T2-weighted fluid attenuated inversion recovery (T2W FLAIR) images could predict prognosis of FCD type III-related refractory epilepsy using a deep learning approach.

Methods

Magnetic resonance imaging (MRI) images of 266 patients with FCD type III diagnosed between 2015 and 2019 were included in this retrospective analysis. A deep learning algorithm utilizing a convolutional neural network (CNN) was trained to classify T2W FLAIR images according to E

SUBMITTER: Wang X 

PROVIDER: S-EPMC9929418 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature