Improved prediction of postoperative pediatric cerebellar mutism syndrome using an artificial neural network.

ABSTRACT:

Background

Postoperative pediatric cerebellar mutism syndrome (pCMS) is a common but severe complication that may arise following the resection of posterior fossa tumors in children. Two previous studies have aimed to preoperatively predict pCMS, with varying results. In this work, we examine the generalization of these models and determine if pCMS can be predicted more accurately using an artificial neural network (ANN).

Methods

An overview of reviews was performed to identify risk factors for pCMS, and a retrospective dataset was collected as per these defined risk factors from children undergoing resection of primary posterior fossa tumors. The ANN was trained on this dataset and its performance was evaluated in comparison to logistic regression and other predictive indic

SUBMITTER: Sidpra J 

PROVIDER: S-EPMC8882257 | biostudies-literature | 2022 Jan-Dec

REPOSITORIES: biostudies-literature