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sift-ms spectra  (Minitab Inc)

 
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    Minitab Inc sift-ms spectra
    Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the <t> SIFT-MS spectra. </t> “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.
    Sift Ms Spectra, supplied by Minitab 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/product/sift-ms+spectra/pmc07591930-133-11-15?v=Minitab+Inc
    Average 90 stars, based on 1 article reviews
    sift-ms spectra - by Bioz Stars, 2026-08
    90/100 stars

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    1) Product Images from "Prediction and detection of human epileptic seizures based on SIFT-MS chemometric data"

    Article Title: Prediction and detection of human epileptic seizures based on SIFT-MS chemometric data

    Journal: Scientific Reports

    doi: 10.1038/s41598-020-75478-8

    Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the SIFT-MS spectra. “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.
    Figure Legend Snippet: Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the SIFT-MS spectra. “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.

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    Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the <t> SIFT-MS spectra. </t> “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.
    Sift Ms Spectra, supplied by Minitab 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/product/sift-ms+spectra/pmc07591930-133-11-15?v=Minitab+Inc
    Average 90 stars, based on 1 article reviews
    sift-ms spectra - by Bioz Stars, 2026-08
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the SIFT-MS spectra. “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.

    Journal: Scientific Reports

    Article Title: Prediction and detection of human epileptic seizures based on SIFT-MS chemometric data

    doi: 10.1038/s41598-020-75478-8

    Figure Lengend Snippet: Confusion matrix for the predicting condition of epileptic patients (classification-tree analysis) based on the SIFT-MS spectra. “Sensitivity” is defined as the percentage of seizure-related spectra that are well predicted by the model, whereas “specificity” is defined as the percentage of non-seizure-related spectra that are correctly rejected.

    Article Snippet: This predictive model was developed from the 1888 variables of the SIFT-MS spectra by using Minitab version 19.2020.1. (Minitab Inc. PA, USA).

    Techniques: