Comparison of multi-algorithm convergence curves. by Chengcheng Ding (9013862)

Table 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

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Table 4_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

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Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

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Table 2_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

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Table 3_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

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Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx by Jingjing Chen (293564)

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Table 3_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx by Weiran Zhang (411189)

Table 2_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx by Weiran Zhang (411189)

Image 3_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif by Weiran Zhang (411189)

Image 2_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif by Weiran Zhang (411189)

Image 1_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.tif by Weiran Zhang (411189)

Table 1_Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.xlsx by Weiran Zhang (411189)

Table 1_Integrated identification of immune-related therapeutic targets for interstitial cystitis via multi-algorithm machine learning: transcriptomic profiling and in vivo experimental validation.docx by Yifan Wang (380120)

Image 2_Integrated identification of immune-related therapeutic targets for interstitial cystitis via multi-algorithm machine learning: transcriptomic profiling and in vivo experimental validation.tif by Yifan Wang (380120)

Image 1_Integrated identification of immune-related therapeutic targets for interstitial cystitis via multi-algorithm machine learning: transcriptomic profiling and in vivo experimental validation.tif by Yifan Wang (380120)

Image 3_Integrated identification of immune-related therapeutic targets for interstitial cystitis via multi-algorithm machine learning: transcriptomic profiling and in vivo experimental validation.tif by Yifan Wang (380120)

Machine learning algorithm performance evaluated by ROC curves. by Man Wang (110466)

Machine learning-driven identification of shared hub genes. by Weiming Cai (135737)

Image 4_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg by Minhao Huang (4952764)

“…A pan-death prognostic signature (Cell-Death Score, CDS), constructed via multi-algorithm machine learning and optimized using CoxBoost to incorporate 25 key genes, demonstrated robust performance in training (1-/3-year AUC = 0.894/0.943) and validation cohort (C-index = 0.717), effectively stratifying high-risk patients (HR = 3.21, p < 0.0001). …”