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Showing 3,321 - 3,335 results of 3,335 for search '(((( algorithm python function ) OR ( algorithm both function ))) OR ( algorithm flow function ))', query time: 0.33s Refine Results
  1. 3321
    Image 3_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 3_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  2. 3322
    Image 9_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 9_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  3. 3323
    Table 2_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx

    Table 2_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

    Published 2025
    “…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”
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  4. 3324
    Image 6_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 6_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  5. 3325
    Image 5_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 5_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  6. 3326
    Data_Sheet_1_Minigene Splicing Assays Identify 12 Spliceogenic Variants of BRCA2 Exons 14 and 15.PDF

    Data_Sheet_1_Minigene Splicing Assays Identify 12 Spliceogenic Variants of BRCA2 Exons 14 and 15.PDF by Eugenia Fraile-Bethencourt (3860176)

    Published 2019
    “…Nine variants affected the natural acceptor or donor sites of both exons and three affected putative enhancers or silencers. …”
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  7. 3327
    Table 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.xlsx

    Table 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  8. 3328
    Table 1_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx

    Table 1_Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.xlsx by Zhiqiang Lin (747094)

    Published 2025
    “…A total of 101 combinations of 10 machine learning algorithms were employed to screen for characteristic RCD-related differentially expressed genes (DEGs) that reflect the progression of MASH. …”
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  9. 3329
    Image 10_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 10_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in pre... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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    Saved in:
  10. 3330
    Image 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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    Saved in:
  11. 3331
    Image 7_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 7_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  12. 3332
    Data from "Minigene splicing assays identify 12 spliceogenic variants of BRCA2 exons 14 and 15"

    Data from "Minigene splicing assays identify 12 spliceogenic variants of BRCA2 exons 14 and 15" by Eladio Andrés Velasco (3369893)

    Published 2019
    “…So, the ESE/ESS prediction algorithms require further improvement.<br><br>…”
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  13. 3333
    Image 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  14. 3334
    EMG and data glove dataset for dexterous myoelectric control

    EMG and data glove dataset for dexterous myoelectric control by Agamemnon Krasoulis (6582983)

    Published 2019
    “…For all participants (i.e. both able-bodied and amputee), the data glove was worn on the left hand (i.e. contralateral to the arm where the EMG sensors were located). …”
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  15. 3335
    FCP dataset for forecasting temperature, PV, price, and load

    FCP dataset for forecasting temperature, PV, price, and load by Hanwen Zhang (18259666)

    Published 2025
    “…</p><p dir="ltr">• To design and develop data-driven algorithms for accurate and reliable charging supplydemand forecasting and cost-optimal scheduling with large-volume and high-resolution data.…”
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