Early diagnosis of Alzheimer's disease based on three-dimensional convolutional neural networks ensemble model combined with genetic algorithm / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 47-55, 2021.
Artículo
en Chino
| WPRIM
| ID: wpr-879248
ABSTRACT
The pathogenesis of Alzheimer's disease (AD), a common neurodegenerative disease, is still unknown. It is difficult to determine the atrophy areas, especially for patients with mild cognitive impairment (MCI) at different stages of AD, which results in a low diagnostic rate. Therefore, an early diagnosis model of AD based on 3-dimensional convolutional neural network (3DCNN) and genetic algorithm (GA) was proposed. Firstly, the 3DCNN was used to train a base classifier for each region of interest (ROI). And then, the optimal combination of the base classifiers was determined with the GA. Finally, the ensemble consisting of the chosen base classifiers was employed to make a diagnosis for a patient and the brain regions with significant classification capability were decided. The experimental results showed that the classification accuracy was 88.6% for AD
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Encéfalo
/
Imagen por Resonancia Magnética
/
Redes Neurales de la Computación
/
Enfermedades Neurodegenerativas
/
Diagnóstico Precoz
/
Enfermedad de Alzheimer
/
Disfunción Cognitiva
Tipo de estudio:
Estudio diagnóstico
/
Estudio pronóstico
/
Estudio de tamizaje
Límite:
Humanos
Idioma:
Chino
Revista:
Journal of Biomedical Engineering
Año:
2021
Tipo del documento:
Artículo
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