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classification-learner package  (MathWorks Inc)


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    Structured Review

    MathWorks Inc classification-learner package
    Characteristics, classification and objectives of the machine learning models used in the studies
    Classification Learner Package, 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/classification-learner package/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    classification-learner package - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review"

    Article Title: Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review

    Journal: BMC Medical Research Methodology

    doi: 10.1186/s12874-025-02463-y

    Characteristics, classification and objectives of the machine learning models used in the studies
    Figure Legend Snippet: Characteristics, classification and objectives of the machine learning models used in the studies

    Techniques Used: Software, Biomarker Discovery, Diagnostic Assay, Imaging, Staining



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    Image Search Results


    Characteristics, classification and objectives of the machine learning models used in the studies

    Journal: BMC Medical Research Methodology

    Article Title: Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review

    doi: 10.1186/s12874-025-02463-y

    Figure Lengend Snippet: Characteristics, classification and objectives of the machine learning models used in the studies

    Article Snippet: Varghese [ ] b , Incidence risk stratification (classification): QSVM (radiomics-based) , Risk stratification for prostate cancer in low- and high-risk patients , desktop-based , CDSS , MATLAB's Classification-Learner Package , NR , NR.

    Techniques: Software, Biomarker Discovery, Diagnostic Assay, Imaging, Staining