Supplementary file 2_Collaborative concept mapping in team-based learning: synthesizing complex immunology concepts in medical education.docx by Dwayne M. Baxa (9018539)

“…However, only 57.8% endorsed concept maps as suitable for a TBL. After implementing feedback-based improvements, more students reported that the activity increased their understanding of immunology (p = 0.018) and microbiology (p = 0.032).…”

Patient satisfaction scores. by Ramona Basnight (17319112)

“…Nursing quality metrics, patient satisfaction, and nursing and nursing assistant turnover were evaluated before and after implementing the role.</p><p>Results</p><p>The online survey showed that nurses and nursing assistants felt that PASAs helped offload their workload, allowing them to focus on nursing-related tasks. …”

Image_2_Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies.JPEG by Liang Xue (174224)

“…</p><p>Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21–34.95, P < 0.001). …”

Table_4_Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies.XLSX by Liang Xue (174224)

“…</p><p>Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21–34.95, P < 0.001). …”

Patient characteristics and procedural data. by Jonathan Nadjiri (665209)

“…Data were acquired for all emergency cases with active arterial bleeding detected in CT scans and the diagnosis to treatment intervals before and after implementation were retrospectively analysed. Time signatures in CT and angiography were used to determine the interval.…”

Table_3_Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies.XLSX by Liang Xue (174224)

“…</p><p>Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21–34.95, P < 0.001). …”

S1 Dataset - by Riham Saud Alhazmy (19697677)

“…</p><p>Results</p><p>The mean HbA1c level decreased from 8.61 ± 1.70 to 7.92 ± 1.60 after implementing the WhatsApp group instructions; the values showed a significant difference (t-value = 5.107 and <i>P</i>-value < 0.001). …”

Particepant recruitment flowchart. by Riham Saud Alhazmy (19697677)

“…</p><p>Results</p><p>The mean HbA1c level decreased from 8.61 ± 1.70 to 7.92 ± 1.60 after implementing the WhatsApp group instructions; the values showed a significant difference (t-value = 5.107 and <i>P</i>-value < 0.001). …”

Data Sheet 4_A clinical predictive model for hearing recovery after middle ear cholesteatoma surgery based on machine learning.zip by Yahui Zhao (7510898)

“…In the validation cohort, the AUC was 0.977 (95% CI 0.82–0.98), and the Hosmer-Lemeshow test revealed X² = 8.54 and p = 0.42. After implementing strict post-split preprocessing to mitigate overfitting and data leakage risks, the model was re-evaluated. …”

Strong effect of demographic changes on Tuberculosis susceptibility in South Africa by Oshiomah P. Oyageshio (19200487)

“…We recruited 1,126 participants with suspected TB from 12 community health clinics and generated a cohort of 774 individuals (cases = 374, controls = 400) after implementing our enrollment criteria. All participants were GeneXpert Ultra tested for active TB by a local clinic. …”

Data Sheet 1_Using machine learning methods to investigate the impact of comorbidities and clinical indicators on the mortality rate of COVID-19.docx by Yueh-Chen Hsieh (22287187)

“…Two versions of the XGBoost model were trained: one incorporating vital signs, suitable for emergency room applications where patients come in with unstable vital signs, and another excluding vital signs, optimized for outpatient settings where we encounter patients with multiple comorbidities. After implementing federated learning, the AUC of the Taipei cohort decreased to 0.90, while the performance of other cohorts improved to meet the required standards. …”

Data Sheet 1_A clinical predictive model for hearing recovery after middle ear cholesteatoma surgery based on machine learning.csv by Yahui Zhao (7510898)

“…In the validation cohort, the AUC was 0.977 (95% CI 0.82–0.98), and the Hosmer-Lemeshow test revealed X² = 8.54 and p = 0.42. After implementing strict post-split preprocessing to mitigate overfitting and data leakage risks, the model was re-evaluated. …”

Data Sheet 3_A clinical predictive model for hearing recovery after middle ear cholesteatoma surgery based on machine learning.pdf by Yahui Zhao (7510898)

“…In the validation cohort, the AUC was 0.977 (95% CI 0.82–0.98), and the Hosmer-Lemeshow test revealed X² = 8.54 and p = 0.42. After implementing strict post-split preprocessing to mitigate overfitting and data leakage risks, the model was re-evaluated. …”

The Forward- and Reverse-Sequence Scan (FRSS) layers and data structures. by Koh Onimaru (265535)

“…An input sequence is scanned by the first convolution kernels, and the kernels are rotated in parallel. After implementing the relu operation, pooling, and the second convolution, the two parallel outputs are combined through summation. …”

Supplementary Material for: Long-Term Noninvasive Ventilation in Chronic Obstructive Pulmonary Disease: Association between Clinical Phenotypes and Survival by Janssens J.-P. (6235223)

“…Probability of death 5 years after implementing NIV was 22.3% (95% CI: 15.4–32.2) for “systemic COPD” versus 47.2% (37.4–59.6) for “respiratory COPD” (<i>p</i> = 0.001). …”

Data Sheet 2_A clinical predictive model for hearing recovery after middle ear cholesteatoma surgery based on machine learning.pdf by Yahui Zhao (7510898)

“…In the validation cohort, the AUC was 0.977 (95% CI 0.82–0.98), and the Hosmer-Lemeshow test revealed X² = 8.54 and p = 0.42. After implementing strict post-split preprocessing to mitigate overfitting and data leakage risks, the model was re-evaluated. …”

Table1_Pharmacist-Urologist Collaborative Management Improves Clinical Outcomes in Patients With Castration-Resistant Prostate Cancer Receiving Enzalutamide.docx by Masaki Hirabatake (12565255)

“…</p><p>Results: After implementing collaborative management, the pharmacists had 881 patient consultations. …”

DataSheet_8_A causal examination of the correlation between hormonal and reproductive factors and low back pain.pdf by Dafu Chen (291913)

“…Subsequently, Multivariate Mendelian randomization (MVMR) was employed to assess the direct causal impact of reproductive and hormone factors on the risk of LBP.</p>Results<p>After implementing the Bonferroni correction and conducting rigorous quality control, the results from MR indicated a noteworthy association between a decreased risk of LBP and AAM (OR=0.784, 95% CI: 0.689-0.891; p=3.53E-04), AFB (OR=0.558, 95% CI: 0.436-0.715; p=8.97E-06), ALB (OR=0.396, 95% CI: 0.226-0.692; p=0.002), and AFS (OR=0.602, 95% CI: 0.518-0.700; p=3.47E-10). …”

DataSheet_2_A causal examination of the correlation between hormonal and reproductive factors and low back pain.pdf by Dafu Chen (291913)

“…Subsequently, Multivariate Mendelian randomization (MVMR) was employed to assess the direct causal impact of reproductive and hormone factors on the risk of LBP.</p>Results<p>After implementing the Bonferroni correction and conducting rigorous quality control, the results from MR indicated a noteworthy association between a decreased risk of LBP and AAM (OR=0.784, 95% CI: 0.689-0.891; p=3.53E-04), AFB (OR=0.558, 95% CI: 0.436-0.715; p=8.97E-06), ALB (OR=0.396, 95% CI: 0.226-0.692; p=0.002), and AFS (OR=0.602, 95% CI: 0.518-0.700; p=3.47E-10). …”

Table_8_A causal examination of the correlation between hormonal and reproductive factors and low back pain.xlsx by Dafu Chen (291913)

“…Subsequently, Multivariate Mendelian randomization (MVMR) was employed to assess the direct causal impact of reproductive and hormone factors on the risk of LBP.</p>Results<p>After implementing the Bonferroni correction and conducting rigorous quality control, the results from MR indicated a noteworthy association between a decreased risk of LBP and AAM (OR=0.784, 95% CI: 0.689-0.891; p=3.53E-04), AFB (OR=0.558, 95% CI: 0.436-0.715; p=8.97E-06), ALB (OR=0.396, 95% CI: 0.226-0.692; p=0.002), and AFS (OR=0.602, 95% CI: 0.518-0.700; p=3.47E-10). …”