The increasing longevity of the population has made Alzheimer's disease (AD) a significant public health concern. However, the challenge of accurately distinguishing different disease stages due to limited variability within the same stage and the potential for errors in manual classification highlights the need for more precise approaches to classifying AD stages. In the field of deep learning, the ResNet50V2 model stands as a testament to its exceptional capabilities in image classification tasks.
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Boudi et al. (2024) studied this question.
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