Table 1_Correlation of triglyceride-glucose index with the incidence and prognosis of hyperglycemic crises in critically ill patients with diabetes mellitus: a machine-learning-bas... by Mingchen Xie (4325692)

“…This study aims to evaluate the relationship between the TyG index and HCE incidence/clinical outcomes in critically ill patients with DM and to construct a risk prediction model using machine-learning algorithms.</p>Methods<p>This multi-center retrospective investigation leveraged clinical repositories from Medical Information Mart for Intensive Care IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD). …”

Supporting data for "Fracture and Non-linear Response of Biopolymer Network with Dynamic Cross-linkers" by Bingxian Tang (9151802)

“…It details the input parameters, such as line density and crosslink number, as well as the algorithms employed for filament arrangement and crosslink determination. …”

Image 4_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.jpeg by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Image 2_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.jpeg by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Image 3_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.jpeg by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Table 1_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.xlsx by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Table 2_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.xlsx by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Image 1_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.jpeg by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Table 3_SCPEP1+ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis.xlsx by Xiang Zhou (164107)

“…Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. …”

Image 1_Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.pdf by Qiang Liu (166143)

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”

Table 1_Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.xlsx by Qiang Liu (166143)

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”