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custom script of matlab for spm  (MathWorks Inc)


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    MathWorks Inc custom script of matlab for spm
    Custom Script Of Matlab For Spm, 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/custom script of matlab for spm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    custom script of matlab for spm - by Bioz Stars, 2026-03
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    Image Search Results


    Maps for all models and real data are shown. The displayed t -statistics range is [0, 8] (colour scale) and is based on the VBM of the real data. The t -statistics were corrected following the procedure used in ref. .

    Journal: Nature Machine Intelligence

    Article Title: Realistic morphology-preserving generative modelling of the brain

    doi: 10.1038/s42256-024-00864-0

    Figure Lengend Snippet: Maps for all models and real data are shown. The displayed t -statistics range is [0, 8] (colour scale) and is based on the VBM of the real data. The t -statistics were corrected following the procedure used in ref. .

    Article Snippet: The VBM SPM MATLAB script templates are available in Supplementary Section .

    Techniques:

    Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

    Journal: Heliyon

    Article Title: A new method applied for explaining the landing patterns: Interpretability analysis of machine learning

    doi: 10.1016/j.heliyon.2024.e26052

    Figure Lengend Snippet: Overview of the proposed workflow for data collection, classification, and explanation in automated landing pattern recognition. A The single-leg landing movements of the subjects before and after the fatigue intervention were collected, and the three-dimensional kinematics and kinetics data of the landing leg during the landing phase were used as the input data of the model. B The three-dimensional kinematics and kinetics data as input signals to explore the recognizability of the two class landing patterns by three classical classification and recognition algorithm models and ZeroR classifier. C The ANN with the best performance in classification and recognition accuracy between classes was used as the forward propagation classifier to compute the input signals, and the output signals of ANN were used as the input of LRP to calculate the RS that can explain the difference of landing patterns through backward propagation. D The application of 1-SPM to evaluate the LRP results from a statistical perspective. E The results of these two aspects were evaluated and discussed together.

    Article Snippet: For the implementation of SPM, the open-source MATLAB script (paired-samples T-test) of One-Dimensional SPM (SPM 1D) was employed to test the statistical differences, and the significance threshold was set as 0.05 [ , ].

    Techniques: