يعرض 1 - 20 نتائج من 7,178 نتيجة بحث عن '(((( learning from decrease ) OR ( _ largest decrease ))) OR ( _ values decrease ))', وقت الاستعلام: 0.37s تنقيح النتائج
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    Supplementary file 1_Early learning curve changes in objective performance indicators during robotic cholecystectomy.docx حسب Derrick Liu (2071018)

    منشور في 2025
    "…As the first study to evaluate objective metrics throughout a learning curve for newly performing robotic cholecystectomy, we identify relevant OPIs that may be critical for future proficiency tracking, 8 of which impact a surgical step with a steep learning curve in transitioning from laparoscopic to robotic cholecystectomy, cystic duct ligation/division.…"
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    TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5<sup>th</sup> and 95<sup>th</sup> percentile change points are determined from 500 bootstrap replicate runs.... حسب Brent J. Bellinger (21156150)

    منشور في 2025
    "…<p>TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5<sup>th</sup> and 95<sup>th</sup> percentile change points are determined from 500 bootstrap replicate runs. …"
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    The MAE value of the model under raw data. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
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    Three error values under raw data. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
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