Predicting cerebral edema in patients with spontaneous intracerebral hemorrhage using machine learning.

ABSTRACT:

Background

The early prediction of cerebral edema changes in patients with spontaneous intracerebral hemorrhage (SICH) may facilitate earlier interventions and result in improved outcomes. This study aimed to develop and validate machine learning models to predict cerebral edema changes within 72 h, using readily available clinical parameters, and to identify relevant influencing factors.

Methods

An observational study was conducted between April 2021 and October 2023 at the Quzhou Affiliated Hospital of Wenzhou Medical University. After preprocessing the data, the study population was randomly divided into training and internal validation cohorts in a 7:3 ratio (training: N = 150; validation: N = 65). The most relevant variables were selected using Support Vec

SUBMITTER: Xu J 

PROVIDER: S-EPMC11484451 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature