Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset.

Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset.

<p>The results from different machine learning methods include: Lasso-Logistic regression <b>(A)</b>, LQV algorithm <b>(B)</b>, Boruta <b>(C)</b>, Bagged Tree <b>(D)</b>, Random Forest <b>(E)</b>, Bayesian <b>(F)</b>, SVM...

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Bibliographic Details
Main Author:	Tianbao Feng (21722233) (author)
Other Authors:	Jiating Hu (10502876) (author), Mi Xie (2065444) (author), Guodong Shi (314927) (author), Qi Wang (22418) (author), Jingyuan Yao (15188771) (author), Xiaoqin Liu (296429) (author)
Published:	2025
Subjects:	Biochemistry Cell Biology Genetics Molecular Biology Immunology Biological Sciences not elsewhere classified spinal cord injury severely impacts motor programmed cell death div >< p debilitating neurological condition promising diagnostic potential potential therapeutic target 707 upregulated genes functional enrichment analysis gene expression omnibus panoptosis scores calculation identify hub genes consistently identified across panoptosis gene sets gene gsea analysis hub genes related gene potential drugs related genes elevated expression targeting panoptosis panoptosis score 23 panoptosis time pcr study seeks significantly higher significant roles significant challenges results underscore rat model quantitative real performed single patient quality pathways associated intersected degs inflammatory response immune response ihc ). healthy controls hc samples future studies experimentally confirm experimental validation emerging concept datasets gse151371 casp5 </ biological functions autonomic functions auc value
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