SpectroCVT-Net: A convolutional vision transformer architecture and channel attention for classifying Alzheimer’s disease using spectrograms-Reference-Cited by-同舟云学术

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SpectroCVT-Net: A convolutional vision transformer architecture and channel attention for classifying Alzheimer’s disease using spectrograms

Published:2024-10 Issue: Volume:181 Page:109022
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Bravo-Ortiz Mario Alejandro,Guevara-Navarro Ernesto^ORCID,Holguín-García Sergio Alejandro,Rivera-Garcia Mariana,Cardona-Morales Oscar^ORCID,Ruz Gonzalo A.,Tabares-Soto Reinel

Funder

Departamento Administrativo de Ciencia, Tecnología e Innovación

Publisher

Elsevier BV

Reference39 articles.

1. Dementia;Organization,2024

2. Diagnosis of early Alzheimer’s disease: clinical practice in 2021;Porsteinsson;J. Prev. Alzheimer’s Dis.,2021

3. Development of a chi-square approach for classifying ischemic stroke prediction;Arowolo,2021

4. MobileNetV1-based deep learning model for accurate brain tumor classification;Mijwil;Mesop. J. Comput. Sci.,2023

5. AI-driven malaria diagnosis: developing a robust model for accurate detection and classification of malaria parasites;Fasihfar;Iran. J. Blood Cancer,2023

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