Table 3_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.docx by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”

Data Sheet 1_Identification of novel lipid metabolism-related biomarkers of aortic dissection by integrating single-cell RNA sequencing analysis and machine learning algorithms.zip by Zhechen Li (15456929)

“…Single-cell RNA sequencing data from aortic dissection and control samples were processed to analyze lipid metabolism activity and identify differentially expressed genes. Machine learning algorithms and protein-protein interaction networks were then used to prioritize biomarkers, which were further validated through bulk RNA-seq analysis and immune infiltration studies and experiments using an Ang II-induced aortic dissection mouse model.. …”

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Classification performances of Ensemble (Subspace KNN), SVM, and KNN algorithms when trained with time domain HbO features. by Ayşenur Eser (21713911)

Evaluating the Vascular Risk of PFCs: An Integrated XGBoost-Driven Structure–Activity Prediction and Experimental Validation Study by Gan Miao (15997685)

Subjects:

Table 1_Differential gene expression profiling and machine learning-based discovery of key genetic markers in VTE and CKD.docx by Hui Li (32376)

“…The intersection of DEGs between VTE and CKD was used for feature selection via three machine learning algorithms: Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine–Recursive Feature Elimination (SVM-RFE), and Random Forest (RF). …”

Comprehensive Climate, Soil, Agronomic, and Management Dataset for Data-Driven Cotton Irrigation in NW China by Liang He (20432320)

Gradient Boosting Trees Machine Learning Approach to Predict the Mutation Types in CaSR. by Aylin Bircan (20176049)

Image 8_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 1_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 7_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 10_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 3_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 6_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 9_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 5_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 4_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Table 1_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.xls by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

Image 2_Integrated bioinformatic analysis and machine learning developed a prognostic model based on mitochondrial function for acute myeloid leukemia.jpeg by Xingbiao Chen (22481431)

“…A total of fourteen machine learning algorithms were employed, yielding 148 unique combinations. …”

GSVA analysis and Immunological analysis. by Xihao Shen (20347942)

Subjects: