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predicting model  (MathWorks Inc)


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    MathWorks Inc predicting model
    Predicting Model, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/predicting model/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    predicting model - by Bioz Stars, 2026-03
    90/100 stars

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    Image Search Results


    Graphical visualisation of the trade-off between patients with septic arthritis not receiving empirical antibiotics versus patients without septic arthritis receiving antibiotics when using the SAS prediction model across different treatment thresholds and the authors’ suggested cut-offs (2% and 10%). “Usual care” is defined by clinician’s choice to treat with empirical antibiotics in the cohort where 4 patients with septic arthritis did not receive intravenous antibiotics and 244 patients without septic arthritis received antibiotics (orange and green dot)

    Journal: BMC Infectious Diseases

    Article Title: Septic arthritis score (SAS) – a novel clinical prediction model for the probability of septic arthritis in the adult native knee

    doi: 10.1186/s12879-025-11306-6

    Figure Lengend Snippet: Graphical visualisation of the trade-off between patients with septic arthritis not receiving empirical antibiotics versus patients without septic arthritis receiving antibiotics when using the SAS prediction model across different treatment thresholds and the authors’ suggested cut-offs (2% and 10%). “Usual care” is defined by clinician’s choice to treat with empirical antibiotics in the cohort where 4 patients with septic arthritis did not receive intravenous antibiotics and 244 patients without septic arthritis received antibiotics (orange and green dot)

    Article Snippet: Fig. 3 Graphical visualisation of the trade-off between patients with septic arthritis not receiving empirical antibiotics versus patients without septic arthritis receiving antibiotics when using the SAS prediction model across different treatment thresholds and the authors’ suggested cut-offs (2% and 10%).

    Techniques: