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processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
batch processing » data processing (Expand Search), speech processing (Expand Search), waste processing (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a while » a whole (Expand Search), a white (Expand Search)
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
batch processing » data processing (Expand Search), speech processing (Expand Search), waste processing (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
a while » a whole (Expand Search), a white (Expand Search)
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81
Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx
Published 2024“…Similarly, for cancer-specific survival (CSS) prediction, the RSF model demonstrated a mean C-index of 0.822, a 5-year AUC of 0.884, and a Brier score of 0.165. …”
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82
Impact of Q on cost analysis diagram.
Published 2025“…Finally, an empirical example was facilitated by examining real shared bikes stations in the Yanta district of Xi’an, China, to verify the effectiveness of the model and algorithm. …”
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83
Stations spatial distribution diagram.
Published 2025“…Finally, an empirical example was facilitated by examining real shared bikes stations in the Yanta district of Xi’an, China, to verify the effectiveness of the model and algorithm. …”
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84
shared bikes distribution vehicle routes diagram.
Published 2025“…Finally, an empirical example was facilitated by examining real shared bikes stations in the Yanta district of Xi’an, China, to verify the effectiveness of the model and algorithm. …”
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85
Stations location and demand.
Published 2025“…Finally, an empirical example was facilitated by examining real shared bikes stations in the Yanta district of Xi’an, China, to verify the effectiveness of the model and algorithm. …”
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86
Table3_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX
Published 2022“…Then, several classifiers were trained and evaluated to obtain optimal classifiers and optimal feature subsets, using three classification algorithms (random forest, k-nearest neighbor, and decision tree) and the incremental feature selection method. …”
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87
Table4_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX
Published 2022“…Then, several classifiers were trained and evaluated to obtain optimal classifiers and optimal feature subsets, using three classification algorithms (random forest, k-nearest neighbor, and decision tree) and the incremental feature selection method. …”
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88
Table1_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX
Published 2022“…Then, several classifiers were trained and evaluated to obtain optimal classifiers and optimal feature subsets, using three classification algorithms (random forest, k-nearest neighbor, and decision tree) and the incremental feature selection method. …”
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89
Table2_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX
Published 2022“…Then, several classifiers were trained and evaluated to obtain optimal classifiers and optimal feature subsets, using three classification algorithms (random forest, k-nearest neighbor, and decision tree) and the incremental feature selection method. …”