Table 1_Machine learning identifies neutrophil extracellular traps-related biomarkers for acute ischemic stroke diagnosis.docx by Haipeng Zhang (3413288)

“…A diagnostic model based on these genes yielded area under the curve (AUC) values of 0.880 in the training dataset and 0.936 in the validation dataset. …”

Table 1_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…The Area Under the Curve (AUC) for the training sets generally ranged from 0.75 to 0.99, which decreased to 0.70 to 0.87 during internal validation. …”

Image 1_Prognostic model construction and immune microenvironment analysis of pyroptosis-related genes in hepatocellular carcinoma based on single-cell RNA sequencing.tiff by Haoming Shen (3816988)

“…The prognostic model developed in this study stratified patients into high-risk and low-risk categories based on eight significant genes, achieving area under the curve (AUC) values of 0.73, 0.65, and 0.69 for overall survival at one-year, two-year, and three-year intervals, respectively. …”

Data Sheet 1_Prognostic model construction and immune microenvironment analysis of pyroptosis-related genes in hepatocellular carcinoma based on single-cell RNA sequencing.zip by Haoming Shen (3816988)

“…The prognostic model developed in this study stratified patients into high-risk and low-risk categories based on eight significant genes, achieving area under the curve (AUC) values of 0.73, 0.65, and 0.69 for overall survival at one-year, two-year, and three-year intervals, respectively. …”

Data Sheet 2_Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.pdf by Lu Ding (475637)

“…Metabolite analysis revealed associations between decreased proline, isoleucine, valine, and alanine levels with IS. …”

Data Sheet 1_Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.pdf by Lu Ding (475637)

“…Metabolite analysis revealed associations between decreased proline, isoleucine, valine, and alanine levels with IS. …”

Data Sheet 3_Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.pdf by Lu Ding (475637)

“…Metabolite analysis revealed associations between decreased proline, isoleucine, valine, and alanine levels with IS. …”

Data Sheet 4_Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.pdf by Lu Ding (475637)

“…Metabolite analysis revealed associations between decreased proline, isoleucine, valine, and alanine levels with IS. …”

Data Sheet 1_Application of machine learning based on habitat imaging and vision transformer to predict treatment response of locally advanced esophageal squamous cell carcinoma fo... by Shu-Han Xie (17902661)

“…Similarly, ExtraTrees showed good predictive capabilities in patients undergoing 2 cycles of nICT with AUC of 0.862 in validation cohort. This model also showed good calibration for prediction probability and satisfied clinical value on DCAs. …”

Image 2_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

Image 1_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

Image 4_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

Image 6_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

Image 3_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

Image 5_Establishment and validation of survival nomogram score staging for esophageal squamous cell carcinoma patients after minimally invasive surgery combined with immune progno... by Shao-jun Xu (11633956)

“…To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). …”

DataSheet1_Early B lymphocyte subsets in blood predict prognosis in sepsis.docx by Yingqian Sun (7843838)

“…Receiver operating characteristic curve analysis showed that B cell subset parameters could predict mortality (area under the receiver operating characteristic curve [AUC], 0.741) and enhanced the prognostic value of the Acute Physiology and Chronic Health Evaluation II score (AUC, 0.840).…”

DataSheet1_Profiling of the serum MiRNAome in pediatric egyptian patients with wilms tumor.PDF by Fatma S. Mohamed (19850220)

“…The ROC curve analysis revealed that multiple dysregulated miRNAs in WT, specifically hsa-miR-7-5p, hsa-miR-146a-5p, hsa-miR-378a-3p, and hsa-miR-483-5p, exhibited high diagnostic potential for WT, with AUC values exceeding 0.86. Among WT histopathology types, the hsa-miR-1180-3p showed a 2.3 log2fold difference in expression between UnFH-WTs and FH-WTs, indicating its potential as a biomarker with 92% sensitivity and 85% specificity for identifying UnFH-WTs. …”

Table_1_Reduced serum neurotrophic factors and monoamine neurotransmitters in epilepsy patients with comorbid depression.DOCX by Shulei Sun (354595)

“…</p>Conclusion<p>The findings suggest the involvement of NTFs, monoamine neurotransmitters, and inflammatory processes in the pathogenesis of epilepsy and depression. Decreased serum BDNF levels correlate with epilepsy but not necessarily with comorbid depression, while serum GDNF and 5-HT show potential clinical value in diagnosing this comorbidity. …”

Attention reduces decision uncertainty under high cognitive demand. by Rahul Garg (3064578)

“…Positive values on the <i>x</i>-axis indicate greater selectivity for CS+ odors. …”

Data Sheet 1_Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients.docx by Xuehang Jin (12419949)

“…Microbiome analysis revealed differential abundances of specific bacterial genera, particularly increased Caulobacter and decreased Acinetobacter in sensitive patients. Notably, serum levels of four bile acids (chenodeoxycholic acid, cholic acid, deoxycholic acid, and ursodeoxycholic acid) were significantly elevated in chemotherapy-sensitive patients, demonstrating good predictive value with AUCs ranging from 0.633 to 0.830.…”