• Mi Re-Unir
    Búsqueda Avanzada
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    Ver ítem 
    •   Inicio
    • UNIR REVISTAS
    • Revista IJIMAI
    • 2021
    • vol. 6, nº 7, september 2021
    • Ver ítem
    •   Inicio
    • UNIR REVISTAS
    • Revista IJIMAI
    • 2021
    • vol. 6, nº 7, september 2021
    • Ver ítem

    Alzheimer Disease Detection Techniques and Methods: A Review

    Autor: 
    Afzal, Sitara
    ;
    Maqsood, Muazzam
    ;
    Khan, Umair
    ;
    Mehmood, Irfan
    ;
    Nawaz, Hina
    ;
    Aadil, Farhan
    ;
    Song, Oh-Young
    ;
    Yunyoung, Nam
    Fecha: 
    09/2021
    Palabra clave: 
    Alzheimer's disease; literature review; mild cognitive impairment; neuroimaging; machine learning; classification; deep learning; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/12997
    DOI: 
    https://doi.org/10.9781/ijimai.2021.04.005
    Dirección web: 
    https://www.ijimai.org/journal/bibcite/reference/2934
    Open Access
    Resumen:
    Brain pathological changes linked with Alzheimer's disease (AD) can be measured with Neuroimaging. In the past few years, these measures are rapidly integrated into the signatures of Alzheimer disease (AD) with the help of classification frameworks which are offering tools for diagnosis and prognosis. Here is the review study of Alzheimer's disease based on Neuroimaging and cognitive impairment classification. This work is a systematic review for the published work in the field of AD especially the computer-aided diagnosis. The imaging modalities include 1) Magnetic resonance imaging (MRI) 2) Functional MRI (fMRI) 3) Diffusion tensor imaging 4) Positron emission tomography (PET) and 5) amyloid-PET. The study revealed that the classification criterion based on the features shows promising results to diagnose the disease and helps in clinical progression. The most widely used machine learning classifiers for AD diagnosis include Support Vector Machine, Bayesian Classifiers, Linear Discriminant Analysis, and K-Nearest Neighbor along with Deep learning. The study revealed that the deep learning techniques and support vector machine give higher accuracies in the identification of Alzheimer’s disease. The possible challenges along with future directions are also discussed in the paper.
    Mostrar el registro completo del ítem
    Ficheros en el ítem
    icon
    Nombre: ijimai6_7_3.pdf
    Tamaño: 1.198Mb
    Formato: application/pdf
    Ver/Abrir
    Este ítem aparece en la(s) siguiente(s) colección(es)
    • vol. 6, nº 7, september 2021

    Estadísticas de uso

    Año
    2012
    2013
    2014
    2015
    2016
    2017
    2018
    2019
    2020
    2021
    2022
    Vistas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    24
    Descargas
    0
    0
    0
    0
    0
    0
    0
    0
    0
    0
    56

    Ítems relacionados

    Mostrando ítems relacionados por Título, autor o materia.

    • On the dynamics of a triparametric family of optimal fourth-order multiple-zero finders with a weight function of the principal mth root of a function-to function ratio 

      Lee, Min-Young; Kim, Young Ik; Magreñán, Á. Alberto (1) (Applied Mathematics and Computation, 12/2017)
      Under the assumption of known root multiplicity m is an element of N, a triparametric family of two-point optimal quartic-order methods locating multiple zeros are investigated in this paper by introducing a weight function ...
    • A biparametric extension of King’s fourth-order methods and their dynamics 

      Geum, Young Hee; Kim, Young Ik; Magreñán, Á. Alberto (1) (Applied Mathematics and Computation, 05/2016)
      A class of two-point quartic-order simple-zero finders and their dynamics are investigated in this paper by extending King’s fourth-order family of methods. With the introduction of an error corrector having a weight ...
    • A study of dynamics via Mobius conjugacy map on a family of sixth-order modified Newton-like multiple-zero finders with bivariate polynomial weight functions 

      Geum, Young Hee; Kim, Young Ik; Magreñán, Á. Alberto (1) (Journal of Computational and Applied Mathematics, 15/12/2018)
      A generic family of sixth-order modified Newton-like multiple-zero finders have been proposed in Geum et al. (2016). Among them we select a specific family of iterative methods with uniparametric bivariate polynomial weight ...

    Mi cuenta

    AccederRegistrar

    ¿necesitas ayuda?

    Manual de UsuarioAutorización TFG-M

    Listar

    todo Re-UnirComunidades y coleccionesPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de accesoEsta colecciónPor fecha de publicaciónAutoresTítulosPalabras claveTipo documentoTipo de acceso






    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja
     
    Aviso Legal Política de Privacidad Política de Cookies Cláusulas legales RGPD
    © UNIR - Universidad Internacional de La Rioja