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plsr prognostic model  (MathWorks Inc)


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    MathWorks Inc plsr prognostic model
    Validation of the Predictive Capability of the <t>PLSR</t> <t>Prognostic</t> Model
    Plsr Prognostic 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/plsr prognostic model/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    plsr prognostic model - by Bioz Stars, 2026-02
    90/100 stars

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    1) Product Images from "Amino acid-based risk stratification model improves prognostic precision in diffuse large B-cell lymphoma"

    Article Title: Amino acid-based risk stratification model improves prognostic precision in diffuse large B-cell lymphoma

    Journal: Cancer Cell International

    doi: 10.1186/s12935-025-03879-8

    Validation of the Predictive Capability of the PLSR Prognostic Model
    Figure Legend Snippet: Validation of the Predictive Capability of the PLSR Prognostic Model

    Techniques Used: Biomarker Discovery



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    Validation of the Predictive Capability of the PLSR Prognostic Model

    Journal: Cancer Cell International

    Article Title: Amino acid-based risk stratification model improves prognostic precision in diffuse large B-cell lymphoma

    doi: 10.1186/s12935-025-03879-8

    Figure Lengend Snippet: Validation of the Predictive Capability of the PLSR Prognostic Model

    Article Snippet: A PLSR prognostic model was established via MATLAB, with repeated training and validation steps, and the prognostic expression for PFS is derived as follows: PFS = 110.2092 + (-5.5576) * Gln + (-6.7974) * Trp + 0.1395 * Age + 3.1042 * Number of extranodal sites + 0.0047 * Number of LDH + (-7.2143) * Number of IPI risk stratifications + (-2.8840) * IPI score.

    Techniques: Biomarker Discovery

    Validation of the Predictive Capability of the PLSR Prognostic Model

    Journal: Cancer Cell International

    Article Title: Amino acid-based risk stratification model improves prognostic precision in diffuse large B-cell lymphoma

    doi: 10.1186/s12935-025-03879-8

    Figure Lengend Snippet: Validation of the Predictive Capability of the PLSR Prognostic Model

    Article Snippet: MATLAB was used to create a partial least squares regression (PLSR) prognostic model and a support vector regression (SVR) machine learning prognostic model.

    Techniques: Biomarker Discovery