بدائل البحث:
surface optimization » surface contamination (توسيع البحث), resource optimization (توسيع البحث), swarm optimization (توسيع البحث)
whole optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
data surface » earth surface (توسيع البحث), metal surface (توسيع البحث), total surface (توسيع البحث)
based whole » used whole (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
surface optimization » surface contamination (توسيع البحث), resource optimization (توسيع البحث), swarm optimization (توسيع البحث)
whole optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
data surface » earth surface (توسيع البحث), metal surface (توسيع البحث), total surface (توسيع البحث)
based whole » used whole (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
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PathOlOgics_RBCs Python Scripts.zip
منشور في 2023"…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …"
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Table_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Image_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Image_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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DataSheet_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.docx
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Image_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Table_4_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Table_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Table_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx
منشور في 2023"…Although the training samples in the optimized set are fewer than in the original set, the prediction precision is almost equivalent to that obtained when using the whole set. …"
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"