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used optimization » based optimization (Expand Search), led optimization (Expand Search), guided optimization (Expand Search)
work optimization » wolf optimization (Expand Search), swarm optimization (Expand Search), dose optimization (Expand Search)
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binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based work » based network (Expand Search)
Showing 1 - 20 results of 59 for search '(( dietary data used optimization algorithm ) OR ( binary based work optimization algorithm ))', query time: 1.12s Refine Results
  1. 1
    One advantage of our algorithm is that it is not binary in nature.

    One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

    Published 2022
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  2. 2
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
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  3. 3
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  4. 4
    Personal details that are used as predictors.

    Personal details that are used as predictors. by Jari Turkia (17912475)

    Published 2024
    “…Considering the limited research on the reactions of ESRD patients, we collected dietary intake data and corresponding laboratory analyses from a cohort of 37 patients. …”
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  5. 5
    Top-performing model configuration and performance by algorithm type.

    Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

    Published 2025
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  6. 6
    Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions.

    Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions. by Jari Turkia (17912475)

    Published 2024
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  7. 7
    Conceptual model for pathways and genes determining cholesterol plasma levels used van de Pas and colleagues [9], [10].

    Conceptual model for pathways and genes determining cholesterol plasma levels used van de Pas and colleagues [9], [10]. by Francesco Reggiani (5727733)

    Published 2020
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  8. 8
    The statistical description of the original data set of the patients (<i>n</i> = 162).

    The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

    Published 2025
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  9. 9
    The list of parameters of the modified data set for machine learning (<i>n</i> = 162).

    The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

    Published 2025
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  10. 10
    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF

    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF by Eva Gonzalez-Flo (5046737)

    Published 2023
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  11. 11
    A* Path-Finding Algorithm to Determine Cell Connections

    A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

    Published 2025
    “…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…”
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  12. 12
    ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.

    ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

    Published 2025
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  13. 13
    The accuracy score change matrix following model development.

    The accuracy score change matrix following model development. by Uğur Ejder (22683228)

    Published 2025
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  14. 14
    The comparison of the accuracy score of the benchmark and the proposed models.

    The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

    Published 2025
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  15. 15
    The prediction accuracy of simple versus hybrid models.

    The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

    Published 2025
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  16. 16
    Flow diagram of the proposed model.

    Flow diagram of the proposed model. by Uğur Ejder (22683228)

    Published 2025
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  17. 17
    Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).

    Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

    Published 2025
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  18. 18
    The most effective active substances for subfertility treatment.

    The most effective active substances for subfertility treatment. by Uğur Ejder (22683228)

    Published 2025
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  19. 19
    Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction.

    Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

    Published 2025
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  20. 20
    Flow diagram of the conversion of drugs into active substances.

    Flow diagram of the conversion of drugs into active substances. by Uğur Ejder (22683228)

    Published 2025
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