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Showing 1 - 20 results of 553 for search '(( gene based prediction optimization algorithm ) OR ( binary based smart optimization algorithm ))', query time: 0.67s Refine Results
  1. 1
    Summary of predictive performance per dataset when using gene-expression predictors.

    Summary of predictive performance per dataset when using gene-expression predictors. by Stephen R. Piccolo (8367780)

    Published 2022
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  2. 2
    Tradeoff between execution time and predictive performance for classification algorithms.

    Tradeoff between execution time and predictive performance for classification algorithms. by Stephen R. Piccolo (8367780)

    Published 2022
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  3. 3
    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization.

    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization. by Stephen R. Piccolo (8367780)

    Published 2022
    “…<p>We predicted patient states using gene-expression and clinical predictors (Analysis 4). …”
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  4. 4
    Summary of predictive performance per dataset when using gene-expression and clinical predictors.

    Summary of predictive performance per dataset when using gene-expression and clinical predictors. by Stephen R. Piccolo (8367780)

    Published 2022
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  5. 5
    DataSheet1_Establishment and Optimization of Radiomics Algorithms for Prediction of KRAS Gene Mutation by Integration of NSCLC Gene Mutation Mutual Exclusion Information.DOCX

    DataSheet1_Establishment and Optimization of Radiomics Algorithms for Prediction of KRAS Gene Mutation by Integration of NSCLC Gene Mutation Mutual Exclusion Information.DOCX by Jingyi Wang (550305)

    Published 2022
    “…<p>Purpose: To assess the significance of mutation mutual exclusion information in the optimization of radiomics algorithms for predicting gene mutation.…”
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  6. 6
    Relative predictive performance when training on gene-expression predictors alone vs. using clinical predictors alone or gene-expression predictors in combination with clinical predictors.

    Relative predictive performance when training on gene-expression predictors alone vs. using clinical predictors alone or gene-expression predictors in combination with clinical pre... by Stephen R. Piccolo (8367780)

    Published 2022
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  7. 7
    Initialization of variables in the APDCA algorithm.

    Initialization of variables in the APDCA algorithm. by Yangsong He (13909371)

    Published 2025
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  8. 8
    Most informative genes for predicting cell-line responses for Gefitinib.

    Most informative genes for predicting cell-line responses for Gefitinib. by Sofia P. Miranda (11418930)

    Published 2021
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  9. 9
    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection with hyperparameter optimization.

    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection with hyperparameter optimization. by Stephen R. Piccolo (8367780)

    Published 2022
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  10. 10
    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection.

    Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection. by Stephen R. Piccolo (8367780)

    Published 2022
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  11. 11
    Relative performance of classification algorithms using gene-expression and clinical predictors and performing feature selection.

    Relative performance of classification algorithms using gene-expression and clinical predictors and performing feature selection. by Stephen R. Piccolo (8367780)

    Published 2022
    “…<p>We predicted patient states using gene-expression and clinical predictors with feature selection (Analysis 5). …”
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  12. 12
    Illustration of the BRIDES algorithm and the selection process.

    Illustration of the BRIDES algorithm and the selection process. by Cindy Bouchard (6844979)

    Published 2022
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  13. 13
    List of ageing-associated genes (STRING identifier and corresponding gene symbol) within imputed genes based on the JenAge Ageing Factor Database for each tissue (brain and liver) and each layer (mRNA and protein) in Ori <i>et al</i>. [13] dataset.

    List of ageing-associated genes (STRING identifier and corresponding gene symbol) within imputed genes based on the JenAge Ageing Factor Database for each tissue (brain and liver)... by Konstantina Charmpi (9901053)

    Published 2021
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  14. 14
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  15. 15
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  16. 16
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  17. 17
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  18. 18
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  19. 19
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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  20. 20
    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance

    Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance by Chunlai Feng (2228515)

    Published 2019
    “…In this study, a gene expression data based deep learning model was developed to predict DILI in advance by using gene expression data associated with DILI collected from ArrayExpress and then optimized by feature gene selection and parameters optimization. …”
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