Comparison of logistic regression and machine learning methods for predicting early neurological deterioration after thrombolysis in patients with mild stroke

We explored the risk factors influencing the occurrence of early neurologic deterioration after thrombolysis in patients with mild stroke. We also found that logistic regression model and machine learning model demonstrated comparable performance in this single-center retrospective dataset.

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Publication Details

Journal
Frontiers in Neurology
Published
2026-03-04
DOI
https://doi.org/10.3389/fneur.2026.1703890
Primary Topic
Acute Ischemic Stroke Management
Type
article
Field-Weighted Citation Impact
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article

Comparison of logistic regression and machine learning methods for predicting early neurological deterioration after thrombolysis in patients with mild stroke

Jin Li, Dongjuan Xu, Meiyun Zhang, Chen Lou
Frontiers in Neurology
Acute Ischemic Stroke Management
article

Comparison of logistic regression and machine learning methods for predicting early neurological deterioration after thrombolysis in patients with mild stroke

Jin Li, Dongjuan Xu, Meiyun Zhang, Chen Lou
article en

Abstract

We explored the risk factors influencing the occurrence of early neurologic deterioration after thrombolysis in patients with mild stroke. We also found that logistic regression model and machine learning model demonstrated comparable performance in this single-center retrospective dataset.

Frontiers in NeurologyVol. 17
Wenzhou Medical University (CN), Dongyang People's Hospital (CN)
Openalex Percentile: Top 35%
Acute Ischemic Stroke Management
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