S1 Data - by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Solution results when p = 8~20. by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Solution results for different case sizes. by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Table of solutions when <i>p</i> = 7~12. by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Definition of variables. by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Raw data of Cell experiments. by Jie Chu (293795)

“…</p><p>Conclusion</p><p>In this study, we developed a risk score based on eight mitochondrial autophagy-related genes and analyzed their expression across different cell types using single-cell analysis. …”

GSEA analysis. by Jie Chu (293795)

“…</p><p>Conclusion</p><p>In this study, we developed a risk score based on eight mitochondrial autophagy-related genes and analyzed their expression across different cell types using single-cell analysis. …”

Baseline data table. by Jie Chu (293795)

“…</p><p>Conclusion</p><p>In this study, we developed a risk score based on eight mitochondrial autophagy-related genes and analyzed their expression across different cell types using single-cell analysis. …”

KEGG analysis. by Jie Chu (293795)

“…</p><p>Conclusion</p><p>In this study, we developed a risk score based on eight mitochondrial autophagy-related genes and analyzed their expression across different cell types using single-cell analysis. …”

Supplementary file 1_Prediction of malignancy risk in Bethesda III nodules: development and validation of multiple machine learning models.pdf by Wentian Li (28857)

“…Objective<p>To develop and validate a machine learning (ML)-based prediction model of Bethesda III nodules and create a nomogram based on the best model.…”

Measuring diaphragmatic excursion using 4-Dimensional Ultrasound: a feasibility study by Adam Handley (21524120)

“…</p><p dir="ltr">This dataset contains Voluson ultrasound data files of diaphragm motion from 12 participants, the raw python code to process this data and the compiled executable of the python scripts. …”

Table 2_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.xlsx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Table 3_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.xlsx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Table 4_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.docx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Data Sheet 1_Development and validation of a predictive model for postoperative functional recovery in patients with spontaneous intracerebral hemorrhage.pdf by Ziming Jiang (9741389)

“…Background<p>This study aimed to develop and validate a prognostic nomogram for predicting 3-month functional recovery in patients undergoing surgery for spontaneous intracerebral hemorrhage (ICH).…”

Table 6_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.xlsx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Table 1_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.docx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Table 5_Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.xlsx by Cunen Wu (12503014)

“…A pan-cancer predictive model for ICI prognosis based on ANSDR.Sig was constructed, with the random forest algorithm yielding the most robust performance. …”

Demographic characteristics of participants. by Tebogo T. Mamalelala (19254175)

“…Descriptive statistics were used to analyse quantitative data, including demographic data. 72 respondents consented and completed the survey, from an estimated 650 staff meeting eligibility criteria; 63% were female and 36% were male. …”

Most common symptom, as reported by respondents. by Tebogo T. Mamalelala (19254175)

“…Descriptive statistics were used to analyse quantitative data, including demographic data. 72 respondents consented and completed the survey, from an estimated 650 staff meeting eligibility criteria; 63% were female and 36% were male. …”