Image 5_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif حسب Hanzhang Lyu (22163404)

"…</p>Methods<p>To address this gap, we constructed a robust prognostic model by integrating over 100 machine learning algorithms—such as LASSO, CoxBoost, and StepCox—based on transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts.…"

ROC Curve for Australian dataset. حسب Al Mahmud Siam (21728789)

"…To validate the proposed approach, we test it on five diverse datasets with varying characteristics and imbalance levels, employing five state-of-the-art machine learning algorithms: Random Forest (RF), Extra Trees (ET), XGBoost (XGBC), AdaBoost, and CatBoost. …"

PR Curve for European cardholder 2023. حسب Al Mahmud Siam (21728789)

"…To validate the proposed approach, we test it on five diverse datasets with varying characteristics and imbalance levels, employing five state-of-the-art machine learning algorithms: Random Forest (RF), Extra Trees (ET), XGBoost (XGBC), AdaBoost, and CatBoost. …"

ROC Curve for European cardholder 2023. حسب Al Mahmud Siam (21728789)

"…To validate the proposed approach, we test it on five diverse datasets with varying characteristics and imbalance levels, employing five state-of-the-art machine learning algorithms: Random Forest (RF), Extra Trees (ET), XGBoost (XGBC), AdaBoost, and CatBoost. …"

PR Curve for European cardholder 2013 (SMOTE). حسب Al Mahmud Siam (21728789)

"…To validate the proposed approach, we test it on five diverse datasets with varying characteristics and imbalance levels, employing five state-of-the-art machine learning algorithms: Random Forest (RF), Extra Trees (ET), XGBoost (XGBC), AdaBoost, and CatBoost. …"

Image 4_A machine learning-derived immune-related prognostic model identifies PLXNA3 as a functional risk gene in colorectal cancer.tif حسب Hanzhang Lyu (22163404)

"…</p>Methods<p>To address this gap, we constructed a robust prognostic model by integrating over 100 machine learning algorithms—such as LASSO, CoxBoost, and StepCox—based on transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts.…"

Computational modeling of platelet activation signatures in response to diverse immune and hemostatic agonists حسب Fabrice Cognasse (78451)

"…Statistical and machine learning methods, including hierarchical clustering and random forest algorithms, were used to classify and interpret the data. …"

Recent benchmark studies. حسب Al Mahmud Siam (21728789)

"…To validate the proposed approach, we test it on five diverse datasets with varying characteristics and imbalance levels, employing five state-of-the-art machine learning algorithms: Random Forest (RF), Extra Trees (ET), XGBoost (XGBC), AdaBoost, and CatBoost. …"

Table 3_Pharmacogenomics and genetic ancestry in Colombia: a study on all variant drug annotations of PharmGKB.xlsx حسب Andy A. Acosta-Monterrosa (22141996)

"…Background<p>To generate an ancestry-resolved pharmacogenomic (PGx) landscape for Colombia by integrating all PharmGKB variant-drug annotations with local allele-frequency data, thereby quantifying inter-ancestry differences of clinical relevance and exposing evidence gaps that hinder equitable precision medicine.…"

Table 1_Associations between metabolic-inflammatory biomarkers and Helicobacter pylori infection: an interpretable machine learning prediction approach.docx حسب Yue Zhang (30585)

"…Decision curve and SHAP analyses supported the clinical relevance of XGB, highlighting Race and Age as dominant contributors.…"

Image 5_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Image 3_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Table 2_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.xlsx حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

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

"…</p>Methods<p>The transcriptomic data from 230 plasma exosomes and 831 HCC tissues were integrated. …"

Image 1_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Image 4_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Table 1_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.xlsx حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Image 2_Single-cell and machine learning-based pyroptosis-related gene signature predicts prognosis and immunotherapy response in glioblastoma.tif حسب Liren Fang (22489516)

"…Pyroptosis activity was quantified by five complementary algorithms, while Monocle2 and Slingshot were employed for pseudotime trajectory reconstruction, and SCENIC was applied for transcription factor network analysis. …"

Image 2_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg حسب Dibash Basukala (20772110)

"…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …"

Image 4_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg حسب Dibash Basukala (20772110)

"…</p>Methods<p>This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1_st order radiomics of IVIM parameters perfusion fraction (f_p), pseudo-diffusion (D_p) and tissue diffusivity (D_t). …"