A Convolutional-based Model for Early Prediction of Alzheimer's based on the Dementia Stage in the MRI Brain Images
This addresses early diagnosis of Alzheimer's disease for adults, potentially reducing disease progression, but appears incremental as it applies existing CNN methods to this domain.
The paper tackled the problem of early Alzheimer's disease diagnosis by proposing a deep convolutional neural network model to determine dementia stages from MRI brain images, aiming to detect early onset, but no concrete results or numbers are provided.
Alzheimer's disease is a degenerative brain disease. Being the primary cause of Dementia in adults and progressively destroys brain memory. Though Alzheimer's disease does not have a cure currently, diagnosing it at an earlier stage will help reduce the severity of the disease. Thus, early diagnosis of Alzheimer's could help to reduce or stop the disease from progressing. In this paper, we proposed a deep convolutional neural network-based model for learning model using to determine the stage of Dementia in adults based on the Magnetic Resonance Imaging (MRI) images to detect the early onset of Alzheimer's.