ArticleComputational and mathematical methods in medicine2022
Construction and Evaluation of Prognosis Prediction Model for Patients with Brain Contusion and Laceration Based on Machine Learning.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- An interpretable multimodal model for early prediction of delayed hematoma progression in frontal lobe contusion: a machine learning approach.Frontiers in neuroscience · 2026Article
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3 authors at 1 institution in 1 country.
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Abstract
Objective: Finding valuable risk factors for the prognosis of brain contusion and laceration can help patients understand the condition and improve the prognosis. This study is aimed at analyzing the risk factors of poor prognosis in patients with brain contusion after the operation. Methods: A total of 136 patients with cerebral contusion and laceration combined with cerebral hernia treated by neurosurgical craniotomy in our hospital were retrospectively selected and divided into a training set ( Results: Based on logistic regression and back-propagation neural network prediction models, GCS score ≤ 8 on admission, blood loss ≥ 30 ml, mannitol ≥ 2 weeks, anticoagulants before admission, and surgical treatment are the risk factors that affect the poor prognosis of patients with a cerebral contusion after the operation. The area under the ROC was 0.816 (95% Conclusion: The prediction model based on the risk factors that affect the poor prognosis of patients with brain contusion and laceration has good discrimination and accuracy.
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