يعرض 1 - 18 نتائج من 18 نتيجة بحث عن '(( gene loss function optimization algorithm ) OR ( binary mask wolf optimization algorithm ))', وقت الاستعلام: 0.56s تنقيح النتائج
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    Table1_Construction of predictive model of interstitial fibrosis and tubular atrophy after kidney transplantation with machine learning algorithms.xlsx حسب Yu Yin (329063)

    منشور في 2023
    "…In this study, 13 machine learning algorithms were used to construct IFTA diagnostic models based on necroptosis-related genes.…"
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    Image1_Construction of predictive model of interstitial fibrosis and tubular atrophy after kidney transplantation with machine learning algorithms.pdf حسب Yu Yin (329063)

    منشور في 2023
    "…In this study, 13 machine learning algorithms were used to construct IFTA diagnostic models based on necroptosis-related genes.…"
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    DataSheet_1_Transcriptome-Based Dissection of Intracranial Aneurysms Unveils an “Immuno-Thermal” Microenvironment and Defines a Pathological Feature-Derived Gene Signature for Risk... حسب Taoyuan Lu (10215872)

    منشور في 2022
    "…Two gene modules recognized via WCGNA were functionally associated with contractile smooth muscle loss and extracellular matrix metabolism, respectively. …"
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    DataSheet_2_Transcriptome-Based Dissection of Intracranial Aneurysms Unveils an “Immuno-Thermal” Microenvironment and Defines a Pathological Feature-Derived Gene Signature for Risk... حسب Taoyuan Lu (10215872)

    منشور في 2022
    "…Two gene modules recognized via WCGNA were functionally associated with contractile smooth muscle loss and extracellular matrix metabolism, respectively. …"
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    Code حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"
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    Core data حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"
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    Table3_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

    منشور في 2022
    "…<p>Cell transplantation is an effective method for compensating for the loss of liver function and improve patient survival. …"
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    Table4_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

    منشور في 2022
    "…<p>Cell transplantation is an effective method for compensating for the loss of liver function and improve patient survival. …"
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    Table1_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

    منشور في 2022
    "…<p>Cell transplantation is an effective method for compensating for the loss of liver function and improve patient survival. …"
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    Table2_Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.XLSX حسب ZhanDong Li (11653330)

    منشور في 2022
    "…<p>Cell transplantation is an effective method for compensating for the loss of liver function and improve patient survival. …"