بدائل البحث:
processing algorithm » modeling algorithm (توسيع البحث), routing algorithm (توسيع البحث), tracking algorithm (توسيع البحث)
elemental learning » evidential learning (توسيع البحث), elemental mapping (توسيع البحث), experiential learning (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
data processing » image processing (توسيع البحث)
processing algorithm » modeling algorithm (توسيع البحث), routing algorithm (توسيع البحث), tracking algorithm (توسيع البحث)
elemental learning » evidential learning (توسيع البحث), elemental mapping (توسيع البحث), experiential learning (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
data processing » image processing (توسيع البحث)
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10881
Table 2_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10882
Table 3_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10883
Table 5_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10884
Table 13_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10885
Table 6_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10886
Table 11_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10887
Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mell...
منشور في 2025"…Patients were randomly assigned to training and validation sets in an 8:2 ratio. Seven ML algorithms were used to construct models in the training set. …"
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10888
Table 1_Integrative multi-omics analysis identifies a PTM-related immune signature and IRF9 as a driver in ccRCC.docx
منشور في 2025"…</p>Methods<p>We intersected immune-related genes, PTM-related genes, and differentially expressed genes in TCGA-KIRC to derive candidates and built a prognostic model across TCGA and E-MTAB-1980 using multiple algorithms, selecting a random survival forest-based post-translational modification-related signature (PTMRS) with the best performance. …"
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10889
Table 7_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10890
Image 1_Integrated analysis of N-glycosylation and Alzheimer’s disease: identifying key biomarkers and mechanisms.tif
منشور في 2025"…</p>Methods<p>A bibliometric analysis of Web of Science literature spanning 2001–2025 was performed using VOSviewer, CiteSpace, and R. Transcriptomic data were analyzed with LIMMA to identify DEGs. …"
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10891
Supplementary file 1_Integrative multi-omics analysis identifies a PTM-related immune signature and IRF9 as a driver in ccRCC.docx
منشور في 2025"…</p>Methods<p>We intersected immune-related genes, PTM-related genes, and differentially expressed genes in TCGA-KIRC to derive candidates and built a prognostic model across TCGA and E-MTAB-1980 using multiple algorithms, selecting a random survival forest-based post-translational modification-related signature (PTMRS) with the best performance. …"
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10892
Table 2_Integrative multi-omics analysis identifies a PTM-related immune signature and IRF9 as a driver in ccRCC.docx
منشور في 2025"…</p>Methods<p>We intersected immune-related genes, PTM-related genes, and differentially expressed genes in TCGA-KIRC to derive candidates and built a prognostic model across TCGA and E-MTAB-1980 using multiple algorithms, selecting a random survival forest-based post-translational modification-related signature (PTMRS) with the best performance. …"
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10893
Table 10_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10894
Table 4_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx
منشور في 2025"…This study aimed to investigate the molecular mechanisms underlying cell and metabolic reprogramming biomarkers in ARDS.</p>Methods<p>Using transcriptomic data from whole blood samples, candidate genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) in conjunction with MRRGs. …"
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10895
An explainable machine learning model in predicting vaginal birth after cesarean section
منشور في 2025"…</p> <p>Models based on ML algorithms can be used to predict VBAC. The CatBoost model showed best performance in this study. …"
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10896
Dataset on impacts of land cover and climate change on Indian birds
منشور في 2024"…Then, an ensemble of machine learning algorithms - random forest, k-nearest neighbour, artificial neural network, support vector machine, and gradient boosting model - were used to project habitat suitability of each species under present conditions (2015) and future scenarios (2100) under two Shared Socio-economic Pathways (SSP3–7.0 and SSP5–8.5). …"
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10897
Image 2_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg
منشور في 2025"…</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<sub>st</sub> order radiomics of IVIM parameters perfusion fraction (f<sub>p</sub>), pseudo-diffusion (D<sub>p</sub>) and tissue diffusivity (D<sub>t</sub>). …"
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10898
Image 4_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg
منشور في 2025"…</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<sub>st</sub> order radiomics of IVIM parameters perfusion fraction (f<sub>p</sub>), pseudo-diffusion (D<sub>p</sub>) and tissue diffusivity (D<sub>t</sub>). …"
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10899
Image 3_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg
منشور في 2025"…</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<sub>st</sub> order radiomics of IVIM parameters perfusion fraction (f<sub>p</sub>), pseudo-diffusion (D<sub>p</sub>) and tissue diffusivity (D<sub>t</sub>). …"
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10900
Image 1_Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study.jpeg
منشور في 2025"…</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<sub>st</sub> order radiomics of IVIM parameters perfusion fraction (f<sub>p</sub>), pseudo-diffusion (D<sub>p</sub>) and tissue diffusivity (D<sub>t</sub>). …"