بدائل البحث:
network optimization » swarm optimization (توسيع البحث), wolf optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
mask network » ms network (توسيع البحث), based network (توسيع البحث), a network (توسيع البحث)
binary aged » binary image (توسيع البحث)
binary mask » binary image (توسيع البحث)
aged based » agent based (توسيع البحث), acid based (توسيع البحث), seed based (توسيع البحث)
network optimization » swarm optimization (توسيع البحث), wolf optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
mask network » ms network (توسيع البحث), based network (توسيع البحث), a network (توسيع البحث)
binary aged » binary image (توسيع البحث)
binary mask » binary image (توسيع البحث)
aged based » agent based (توسيع البحث), acid based (توسيع البحث), seed based (توسيع البحث)
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A* Path-Finding Algorithm to Determine Cell Connections
منشور في 2025"…To address this, the research integrates a modified A* pathfinding algorithm with a U-Net convolutional neural network, a custom statistical binary classification method, and a personalized Min-Max connectivity threshold to automate the detection of astrocyte connectivity.…"
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SHAP bar plot.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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Sample screening flowchart.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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Descriptive statistics for variables.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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SHAP summary plot.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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ROC curves for the test set of four models.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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Display of the web prediction interface.
منشور في 2025"…Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"
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Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
منشور في 2022"…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"
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Image processing workflow.
منشور في 2020"…All image segments of cell clusters were standardized to the same size with either (b) Null Bumper, (b) Blended or (d) Masked methods. These annotated training images were passed to the cCNN to determine optimal network weights (e). …"
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DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"