Table 1_Plasma exosomal lncRNA-related signatures define molecular subtypes and predict survival and treatment response in hepatocellular carcinoma.docx حسب Fangmin Zhong (17415318)

"…Prognostic models were developed and optimized via 10 machine learning algorithms with 10-fold cross-validation. …"

CANDID-II Dataset حسب Sijing Feng (10187216)

"…This dataset can be used for training and testing for deep learning algorithms for adult chest x rays.</p><p dir="ltr">Unfortunately, since Feb 2024, the New Zealand government is changing the data governance on datasets used for AI development and this affects the process of how the CANDID II dataset is to be accessed by the external users. …"

Table 2_Artificial intelligence in vaccine research and development: an umbrella review.docx حسب Rabie Adel El Arab (14113425)

"…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…"

Table 3_Artificial intelligence in vaccine research and development: an umbrella review.docx حسب Rabie Adel El Arab (14113425)

"…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…"

Table 1_Artificial intelligence in vaccine research and development: an umbrella review.docx حسب Rabie Adel El Arab (14113425)

"…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…"

Table 3_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xlsx حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Image 3_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Image 4_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Table 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xlsx حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Image 1_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Table 2_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xls حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Table 4_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.xlsx حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

Image 2_Unveiling ammonia-induced cell death: a new frontier in clear cell renal cell carcinoma prognosis.tif حسب Peize Yu (21837977)

"…Differentially expressed AICD-related genes were identified through differential expression analysis, univariate Cox regression, and machine learning algorithms (LASSO, random forest, and CoxBoost). A prognostic risk model was developed via multivariate Cox regression. …"

CANDID-III Dataset حسب Sijing Feng (10187216)

"…This dataset can be used for training and testing for deep learning algorithms for adult chest x rays.</p><p dir="ltr">Unfortunately, since Feb 2024, the New Zealand government is changing the data governance on datasets used for AI development and this affects the process of how the CANDID III dataset is to be accessed by the external users. …"

Table1_Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean.xlsx حسب Jérôme Gélinas Bélanger (17929694)

"…The E8-r3 locus is a genomic region regulating the number of days to maturity under constant short-day photoperiodic conditions in two early-maturing soybean populations (QS15524_F2:F3 and QS15544_RIL) belonging to maturity groups MG00 and MG000. In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus (Glyma.04G167900/GmLHCA4a, Glyma.04G166300/GmPRR1a, and Glyma.04G159300/GmMDE04). …"

Image1_Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean.jpeg حسب Jérôme Gélinas Bélanger (17929694)

"…The E8-r3 locus is a genomic region regulating the number of days to maturity under constant short-day photoperiodic conditions in two early-maturing soybean populations (QS15524_F2:F3 and QS15544_RIL) belonging to maturity groups MG00 and MG000. In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus (Glyma.04G167900/GmLHCA4a, Glyma.04G166300/GmPRR1a, and Glyma.04G159300/GmMDE04). …"

Image2_Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean.jpeg حسب Jérôme Gélinas Bélanger (17929694)

"…The E8-r3 locus is a genomic region regulating the number of days to maturity under constant short-day photoperiodic conditions in two early-maturing soybean populations (QS15524_F2:F3 and QS15544_RIL) belonging to maturity groups MG00 and MG000. In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus (Glyma.04G167900/GmLHCA4a, Glyma.04G166300/GmPRR1a, and Glyma.04G159300/GmMDE04). …"

Image 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif حسب Bin He (75597)

"…In the electrical remodeling investigation, ion channel gene sets and gene expression data were utilized alongside LASSO and SVM machine-learning algorithms combined with ROC curve analysis. …"

Table 3_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx حسب Bin He (75597)

"…In the electrical remodeling investigation, ion channel gene sets and gene expression data were utilized alongside LASSO and SVM machine-learning algorithms combined with ROC curve analysis. …"

Table 8_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.xlsx حسب Bin He (75597)

"…In the electrical remodeling investigation, ion channel gene sets and gene expression data were utilized alongside LASSO and SVM machine-learning algorithms combined with ROC curve analysis. …"