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Título
Deep learning neural network for Alzheimer’s disease predictions
Autor
Facultad/Centro
Área de conocimiento
Es parte de
Domínguez González, M., Cabrera Santana, P. J., Irigoyen Gordo, E. (eds.) (2022). XVII Simposio CEA de Control Inteligente: Reunión anual del grupo de Control Inteligente del comité español de automática (CEA). Libro de Actas, León, 27-29 de junio de 2022
Cita Bibliográfica
Alyaqoobi, H. I., Lopez-Guede, J. M., Akbar, O. A., Rahebi, J. (2022). Deep learning neural network for Alzheimer’s disease predictions. XVII Simposio CEA de Control Inteligente: Reunión anual del grupo de Control Inteligente del comité español de automática (CEA). Libro de Actas, León, 27-29 de junio de 2022. 101-103
Editorial
Universidad de León
Fecha
2022
Resumen
[EN] Alzheimer's disease is a dangerous and progressive disease that affects the nervous system and brain of people. An important and effective approach to treating Alzheimer's disease is to diagnose the disease early so that more effective treatments can be offered. One practical way to diagnose Alzheimer's disease is to use magnetic resonance imaging to detect plaque and affected areas. In this paper, a new method based on the Harris Hawks optimization method is presented for Alzheimer’s disease diagnosis. This method uses the best features that obtain from the MRI images and uses it in deep learning to classify the healthy and non-healthy images.
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