Predictive models for secondary epilepsy in patients with acute ischemic stroke within one year

Predictive models for secondary epilepsy in patients with acute ischemic stroke within one year

Background: Post-stroke epilepsy (PSE) is a critical complication that worsens both prognosis and quality of life in patients with ischemic stroke. An interpretable machine learning model was developed to predict PSE using medical records from four hospitals in Chongqing. Methods: Medical records, i...

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Bibliographic Details
Main Authors: Jinxin Liu, Haoyue He, Yanglingxi Wang, Jun Du, Kaixin Liang, Jun Xue, Yidan Liang, Peng Chen, Shanshan Tian, Yongbing Deng
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2024-11-01
Series:eLife
Subjects:
stroke
epilepsy
machine learning
Online Access:https://elifesciences.org/articles/98759
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