Construction of non-invasive diagnostic model and nomogram of AR.

A. Expression profiles of 13pSRGs in peripheral blood datasets. Four genes that were differentially expressed in both datasets are highlighted in red. B. ROC curves evaluating the performances of the models. RF model was ultimately selected. C....

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Bibliographic Details
Main Author:	Xihao Shen (20347942) (author)
Other Authors:	Jiyue Wu (3814717) (author), Feilong Zhang (420300) (author), Qing Bi (3864823) (author), Zejia Sun (10031646) (author), Wei Wang (17594) (author)
Published:	2024
Subjects:	Cell Biology Genetics Molecular Biology Neuroscience Biotechnology Developmental Biology Marine Biology Cancer Virology Computational Biology weighted gene co two clusters underscored multiple established databases machine learning algorithms integrative machine learning gene expression omnibus demographic shift towards consensus clustering algorithm b >(</ b aged donor kidneys term graft outcomes expression network analysis differential expression analysis comprehensive analysis underscores worse graft survival reduced graft survival predicting graft survival two rejection clusters rejection remains elusive optimal acute rejection delayed graft function ktx rejection poses ktx rejection occurrence identify predictive srgs invasive diagnostic model kidney transplant rejection graft survival ktx rejection kidney graft diagnostic model kidney rejection gsva analysis cluster analysis allograft function rejection samples diagnosing rejection prognostic model kidney transplantation xlink "> wgcna ), significant threat related genes provided microarray positive correlation level landscape ischemic damage detailed cellular conducted using conclusions drawn cluster c1 c2 ).
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Construction of non-invasive diagnostic model and nomogram of AR.

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