Showing 1 - 20 results of 26 for search '(( ct ((largest decrease) OR (larger decrease)) ) OR ( _ knn decrease ))', query time: 0.43s Refine Results
  1. 1

    Hybrid imputation of missing values using KNN on MEWMA-based adaptive process control by Yijun Jiang (1852231)

    Published 2025
    “…When dealing with data fluctuation, we assign a higher weight to the KNN method for its sensitivity, while the EWMA method is preferred for stationary data. …”
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    Data Sheet 1_Correlation analysis of osteoporosis and vertebral endplate defects using CT and MRI imaging: a retrospective cross-sectional study.pdf by Song Hao (5700608)

    Published 2025
    “…</p>Methods<p>Computed tomography (CT), magnetic resonance imaging (MRI), bone mineral density (BMD) and other relevant imaging data, as well as age, sex, body mass index (BMI), and degree of low back pain data, were retrospectively analysed. …”
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    Data Sheet 1_Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds.csv by Vittoria Asti (14490794)

    Published 2024
    “…Introduction<p>The shift of the horse breeding sector from agricultural to leisure and sports purposes led to a decrease in local breeds’ population size due to the loss of their original breeding purposes. …”
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    Data Sheet 2_Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds.docx by Vittoria Asti (14490794)

    Published 2024
    “…Introduction<p>The shift of the horse breeding sector from agricultural to leisure and sports purposes led to a decrease in local breeds’ population size due to the loss of their original breeding purposes. …”
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    Image 2_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

    Published 2025
    “…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. It is highly prevalent and has a harsh impact on patients' lives. …”
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    Table 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.docx by Jiaming Wang (2637667)

    Published 2025
    “…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. It is highly prevalent and has a harsh impact on patients' lives. …”
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    Image 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

    Published 2025
    “…Background<p>Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. It is highly prevalent and has a harsh impact on patients' lives. …”
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    3-D burrow morphology of <i>Chondrites targionii</i> (Brongniart, 1828) from an Upper Jurassic firmground of Southern Germany by Franz-Josef Scharfenberg (13134765)

    Published 2025
    “…Eleven identified burrow portions are likely parts of three larger burrow systems. With intermediate effect size, statistically compared branch widths revealed significantly decreasing widths from unbranched tunnels over root branches to their side branches, which, along with the scale-leaf-shaped structures, may indicate a vermiform tracemaker. …”
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    Raw data underlying the findings in this study. by Andrew Mvula (20161161)

    Published 2024
    “…On average, male Three-lips fish are larger in length and weight than females, and in many species, females prefer larger males to smaller males, viewing their size as an indicator of genetic fitness and their ability to provide protection. …”
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    Supplementary file 1_Application of multidimensional gait feature fusion algorithm in gait assessment for patients with knee osteoarthritis.docx by Yuzhe Tan (22274731)

    Published 2025
    “…Machine learning models including Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), and k- Nearest Neighbors (KNN) were employed for gait classification and assessment.…”
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    Demographic and ocular features. by Mingxi Shao (10066570)

    Published 2025
    “…Positive correlations were also significant: MDA with axial length (AL (r = 0.576, p = 0.002). The XGBoost or KNN model using TAS alone achieved the highest AUC (0.74) in five-fold cross-validation.…”
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    Machine learning model to diagnose PCG. by Mingxi Shao (10066570)

    Published 2025
    “…Positive correlations were also significant: MDA with axial length (AL (r = 0.576, p = 0.002). The XGBoost or KNN model using TAS alone achieved the highest AUC (0.74) in five-fold cross-validation.…”
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    ROC curves of TAS + SOD + MDA to diagnose PCG. by Mingxi Shao (10066570)

    Published 2025
    “…Positive correlations were also significant: MDA with axial length (AL (r = 0.576, p = 0.002). The XGBoost or KNN model using TAS alone achieved the highest AUC (0.74) in five-fold cross-validation.…”
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    Data Sheet 2_Effect of thyme-ivy syrup on antiviral immune response in patients with mild COVID-19: a prospective, open-label, randomized pilot study.docx by Stephanie Dauth (13274397)

    Published 2025
    “…</p>Methods<p>This prospective, open-label, randomized, controlled, single-center pilot study (BroVID study; EudraCT 2021–003237-11) was conducted in adult outpatients with mild COVID-19, cough, and ≥1 additional symptom. …”
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    Data Sheet 1_Effect of thyme-ivy syrup on antiviral immune response in patients with mild COVID-19: a prospective, open-label, randomized pilot study.docx by Stephanie Dauth (13274397)

    Published 2025
    “…</p>Methods<p>This prospective, open-label, randomized, controlled, single-center pilot study (BroVID study; EudraCT 2021–003237-11) was conducted in adult outpatients with mild COVID-19, cough, and ≥1 additional symptom. …”
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    Data Sheet 2_UrbanAgri: a transfer learning-based plant stress identification framework for sustainable smart urban growth.pdf by Upinder Kaur (10805317)

    Published 2025
    “…<p>The speed of urbanization around the world is decreasing the arable land endangering food security since the population is estimated to reach 9.7 billion by the year 2050. …”