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Showing 1 - 20 results of 33 for search '(( primary made using optimization algorithm ) OR ( binary _ codon optimization algorithm ))', query time: 0.36s Refine Results
  1. 1
    GBO framework used to estimate the battery SOH.

    GBO framework used to estimate the battery SOH. by Mouncef El Marghichi (17328361)

    Published 2023
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  2. 2
    Consort diagram for the study.

    Consort diagram for the study. by Nicola Lazzarini (3528197)

    Published 2022
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  3. 3
    Performance confidence intervals.

    Performance confidence intervals. by Nicola Lazzarini (3528197)

    Published 2022
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  4. 4
    Baseline characteristics of patients in the study cohort.

    Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

    Published 2022
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  5. 5
    Input features.

    Input features. by Nicola Lazzarini (3528197)

    Published 2022
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  6. 6
    Most important predictive features.

    Most important predictive features. by Nicola Lazzarini (3528197)

    Published 2022
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  7. 7
    Age feature importance.

    Age feature importance. by Nicola Lazzarini (3528197)

    Published 2022
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  8. 8
    Machine learning vs. clinicians.

    Machine learning vs. clinicians. by Nicola Lazzarini (3528197)

    Published 2022
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  9. 9
    ROC curves.

    ROC curves. by Nicola Lazzarini (3528197)

    Published 2022
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  10. 10
    PR curves.

    PR curves. by Nicola Lazzarini (3528197)

    Published 2022
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  11. 11
    Overview of the cohort definition process.

    Overview of the cohort definition process. by Nicola Lazzarini (3528197)

    Published 2022
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  12. 12
    Data used in this study.

    Data used in this study. by Qinghua Li (398885)

    Published 2024
    “…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”
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  13. 13
    ECE6379_PSOM.zip

    ECE6379_PSOM.zip by Xingpeng Li (11825663)

    Published 2021
    “…Optimization algorithms that are commonly used to solve these problems will also be covered including linear programming, mixed-integer linear programming, Lagrange relaxation, dynamic programming, branch and bound, and duality theory.…”
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  14. 14
    Table_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.docx

    Table_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.docx by Jiang Zhu (40858)

    Published 2021
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  15. 15
    Image_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.TIFF

    Image_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.TIFF by Jiang Zhu (40858)

    Published 2021
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  16. 16
    Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model

    Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model by Ali Aminian (9580734)

    Published 2020
    “…A total of 1682 amine + CO<sub>2</sub> + water viscosity data sets for primary, secondary, and tertiary amines and 220 data points for further accuracy examinations were used. …”
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  17. 17
    Table_2_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DOCX

    Table_2_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DO... by Kuo-Yang Huang (4470730)

    Published 2023
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  18. 18
    Table_3_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DOCX

    Table_3_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DO... by Kuo-Yang Huang (4470730)

    Published 2023
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  19. 19
    Table_1_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DOCX

    Table_1_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.DO... by Kuo-Yang Huang (4470730)

    Published 2023
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  20. 20
    Data_Sheet_1_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters.docx

    Data_Sheet_1_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived paramete... by Kuo-Yang Huang (4470730)

    Published 2023
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