Table 1_Analysis of risk factors and development of a prediction model for long-term prognosis in patients with ischemic heart failure after percutaneous coronary intervention.docx by Lifang Su (22500584)

“…Calibration curve and decision curve analysis demonstrated the model's consistency and clinical utility. The external validation of the model yielded an AUC of 0.707, and the C-index was 0.691. …”

Table 1_Identification of NPM and non-mass breast cancer based on radiological features and radiomics.docx by Zhen Guo (68566)

“…</p>Results<p>Calcification type and asymmetric dense shadows differed significantly between NPM and non-mass breast cancer (P < 0.05). …”

Table 2_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Image 3_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Table 1_A novel automated CT biomarker to predict outcomes in acute ischemic stroke: net water uptake.docx by Monica Mallavarapu (22106330)

“…The ASPECTS-based model performance was not significantly different from the NWU-based model to classify 90-day mRS outcome, with AUROC 0.732 and 0.749, respectively, (p = 0.513 with Delong test). …”

Table_1_Survival prediction for heart failure complicated by sepsis: based on machine learning methods.DOCX by Qitian Zhang (19791372)

“…Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.</p>…”

Image 2_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Image_3_Survival prediction for heart failure complicated by sepsis: based on machine learning methods.TIF by Qitian Zhang (19791372)

“…Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.</p>…”

Table 1_Development and validation of deep learning- and ensemble learning-based biological ages in the NHANES study.docx by Yushu Huang (4540804)

“…This study aims to develop and validate novel ML-based BA models using a comprehensive set of clinical, behavioral, and socioeconomic factors and evaluate their predictive performance for mortality.…”

Data_Sheet_1_Survival prediction for heart failure complicated by sepsis: based on machine learning methods.ZIP by Qitian Zhang (19791372)

“…Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.</p>…”

Image 1_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Scheme of inclusion of participants in the study. by Syed Muhammad Tauseef Shafqat (22250852)

“…Data regarding clinical manifestations revealed the highest frequency (87.50%) of fatigue with general weakness and the lowest one of night sweats (20.83%) in seropositive women.…”

Table 1_Assessing the prognostic value of serum creatinine to cystatin C ratio in stage III-IV colorectal cancer: development of a nutritional prognostic scoring system.docx by Weicheng Ji (22465039)

“…This study aims to investigate the prognostic significance of CCR and develop a nutritional prognostic scoring system based on CCR.…”

Supplementary Material for: Association between Salivary pH and estimated glomerular filtration rate status in a community-dwelling population: A Cross-sectional Study by figshare admin karger (2628495)

“…The pH model showed accuracy comparable to that of BUN model in determining the eGFR status (area under the curve for the pH and BUN models was 0.796 and 0.799, respectively; P = 0.933). …”

Image_1_Survival prediction for heart failure complicated by sepsis: based on machine learning methods.TIF by Qitian Zhang (19791372)

“…Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.</p>…”

Table 1_Prognostic value of inflammatory markers for all-cause mortality in patients with acute myocardial infarction in the coronary care unit: a retrospective study based on MIMI... by Fen Cao (4496014)

“…</p>Methods<p>Adult patients diagnosed with AMI and admitted to CCU were selected from the MIMIC-IV database. Various clinical and laboratory data were extracted. Logistic regression models were employed to determine the correlation between NLR and in-hospital mortality, 30-day mortality, and 90-day mortality. …”

Image_2_Survival prediction for heart failure complicated by sepsis: based on machine learning methods.TIF by Qitian Zhang (19791372)

“…Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.</p>…”

Image 5_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Image 4_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”

Table 1_Effect of different blood flow restriction training regimens combined with low-intensity training on muscle strength and cardiovascular safety in older adults: a systematic... by Meiling Ren (1332204)

“…The results of this network meta-analysis showed that: 1) in terms of improving muscle strength: compared to the controls, low-frequency, low-pressure, and low-intensity BFR training regimen was significantly related to one-repetition maximum (1RM) strength [weighted mean difference (WMD) = 0.58, 95% CI: 0.81–1.08 P < 0.05]. …”