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    Home > Active Ingredient News > Study of Nervous System > JNNP: Predicting temporal lobe epilepsy surgical outcome using diffusion imaging

    JNNP: Predicting temporal lobe epilepsy surgical outcome using diffusion imaging

    • Last Update: 2022-04-24
    • Source: Internet
    • Author: User
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    Epilepsy is one of the most common disabling neurological disorders in patients over the age of 50


    Epilepsy is one of the most common disabling neurological disorders in patients over the age of 50


    Many researchers use machine learning (aka artificial intelligence) to address problems in epilepsy using information gleaned from non-invasive modalities


    151 subjects (62 TLE patients and 89 healthy controls) were included in the analysis


    151 subjects (62 TLE patients and 89 healthy controls) were included in the analysis


    Binary Decision Trees for TLE Diagnosis and Prognosis

    Binary Decision Trees for TLE Diagnosis and Prognosis

    Using the fully hold-out test dataset, the technique classified TLE patients versus healthy controls with an AUC of 0.


    Using the fully hold-out test dataset, the technique classified TLE patients versus healthy controls with an AUC of 0.


    Decoding network predicts temporal lobe epilepsy (TLE)

    Decoding network predicts temporal lobe epilepsy (TLE)

    Advanced neuroimaging analysis can be effectively used to enhance current clinically driven predictive models


    Advanced neuroimaging analysis can be effectively used to enhance current clinically driven predictive models


    This technique classifies important clinical decisions in preoperative examination of temporal lobe epilepsy by generating clear white matter features




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