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sera package  (MathWorks Inc)


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    Structured Review

    MathWorks Inc sera package
    Neural <t>network-RADIOMICS</t> architecture.
    Sera 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/sera package/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    sera package - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis"

    Article Title: Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis

    Journal: Nuclear Medicine Communications

    doi: 10.1097/MNM.0000000000001810

    Neural network-RADIOMICS architecture.
    Figure Legend Snippet: Neural network-RADIOMICS architecture.

    Techniques Used:

    Probability score for a subject to be normal or pathological for various types of dementia
    Figure Legend Snippet: Probability score for a subject to be normal or pathological for various types of dementia

    Techniques Used: Biomarker Discovery



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    Image Search Results


    Neural network-RADIOMICS architecture.

    Journal: Nuclear Medicine Communications

    Article Title: Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis

    doi: 10.1097/MNM.0000000000001810

    Figure Lengend Snippet: Neural network-RADIOMICS architecture.

    Article Snippet: The Standardized Environment for Radiomics Analysis (SERA) Package [ ] (a Matlab-based framework) was used for this purpose, in which features are consistent with the guidelines of Image Biomarker Standardization Initiative.

    Techniques:

    Probability score for a subject to be normal or pathological for various types of dementia

    Journal: Nuclear Medicine Communications

    Article Title: Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis

    doi: 10.1097/MNM.0000000000001810

    Figure Lengend Snippet: Probability score for a subject to be normal or pathological for various types of dementia

    Article Snippet: The Standardized Environment for Radiomics Analysis (SERA) Package [ ] (a Matlab-based framework) was used for this purpose, in which features are consistent with the guidelines of Image Biomarker Standardization Initiative.

    Techniques: Biomarker Discovery