يعرض 1 - 20 نتائج من 44 نتيجة بحث عن '(( primary screen model optimization algorithm ) OR ( binary mapk driven optimization algorithm ))', وقت الاستعلام: 0.78s تنقيح النتائج
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    Table_1_Screening of Long Non-coding RNAs Biomarkers for the Diagnosis of Tuberculosis and Preliminary Construction of a Clinical Diagnosis Model.docx حسب Juli Chen (12187358)

    منشور في 2022
    "…Background<p>Pathogenic testing for tuberculosis (TB) is not yet sufficient for early and differential clinical diagnosis; thus, we investigated the potential of screening long non-coding RNAs (lncRNAs) from human hosts and using machine learning (ML) algorithms combined with electronic health record (EHR) metrics to construct a diagnostic model.…"
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    Consort diagram for the study. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Performance confidence intervals. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Input features. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Most important predictive features. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Age feature importance. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Machine learning vs. clinicians. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    ROC curves. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    PR curves. حسب Nicola Lazzarini (3528197)

    منشور في 2022
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    Table_1_One-Time Optimization of Advanced T Cell Culture Media Using a Machine Learning Pipeline.DOCX حسب Paul Grzesik (11136582)

    منشور في 2021
    "…When optimizing culture media for primary cells used in cell and gene therapy, traditional DoE approaches that depend on interpretable models will not always provide reliable predictions due to high donor variability. …"
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    Image_1_A cost-effective, machine learning-driven approach for screening arterial functional aging in a large-scale Chinese population.JPEG حسب Rujia Miao (12075653)

    منشور في 2024
    "…Four machine learning algorithms were applied to build the screening models for elevated arterial stiffness (EAS), and the performance of models was evaluated by calculating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.…"