Image 3_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.jpeg by Jiafeng Peng (22116253)

“…Subsequently, nomograms, functional enrichment analyses, immune infiltration analyses, regulatory network construction, drug prediction, and molecular docking were performed to characterize the functional and clinical significance of the biomarkers. …”

Table 10_Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data.csv by Jiafeng Peng (22116253)

“…Subsequently, nomograms, functional enrichment analyses, immune infiltration analyses, regulatory network construction, drug prediction, and molecular docking were performed to characterize the functional and clinical significance of the biomarkers. …”

Data Sheet 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Table 4_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Table 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Image 1_Immune-molecular nexus in reproductive disorders: mechanisms linking POI and RSA.pdf by Chen Chen (6544)

“…The analysis involved machine learning algorithms, mcode and Cytoscape, revealing important hub genes. …”

Data Sheet 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.pdf by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Supplementary file 1_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Table 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Supplementary file 2_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Table 3_Novel diagnostic biomarkers associated with macrophage-microglia in spinal cord injury.xlsx by Manyi Zheng (22221913)

“…Predictive models based on these genes demonstrated strong performance in both internal training and external validation cohorts. …”

Table 2_Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning.docx by Jinyu Zheng (734257)

“…Three machine learning algorithms—Random Forest, LASSO, and SVM-RFE—were applied to identify key hub genes. …”

Table 1_Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning.docx by Jinyu Zheng (734257)

“…Three machine learning algorithms—Random Forest, LASSO, and SVM-RFE—were applied to identify key hub genes. …”

Table 2_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx by Kai Lu (166354)

“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”

Supplementary file 1_Transcriptomic analysis and machine learning modeling identifies novel biomarkers and genetic characteristics of hypertrophic cardiomyopathy.xlsx by Feng Zhang (6548)

“…A predictive model for HCM was developed through systematic evaluation of 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on training datasets and external validation using an independent cohort (GSE180313).…”

Supplementary file 1_Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study.docx by Yejing Zhao (22123588)

“…However, there is still a notable absence of novel biomarkers that are both efficient, minimally invasive, and cost-effective in real-world clinical settings. …”

Table 1_Comprehensive analysis of immunogenic cell death-related genes in liver ischemia-reperfusion injury.xlsx by Kai Lu (166354)

“…The RF and SVM machine learning algorithms were finally chosen to construct the models. …”

Image1_Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.pdf by Lei Zhong (192135)

“…Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. …”

Table1_Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.xlsx by Lei Zhong (192135)

“…Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. …”

Supplementary file 1_Identification of glycolysis-related clusters and immune cell infiltration in hepatic fibrosis progression using machine learning models and experimental valid... by Guanglin Xiao (18113302)

“…Integrated weighted gene co-expression network analysis (WGCNA) with six machine learning algorithms to identify core GRGs genes associated with HF progression, and systematically characterized their biological functions and immunoregulatory roles through immune infiltration assessment, functional enrichment, consensus clustering, and single-cell differential state analysis. …”