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Researchers from Qufu Normal University in China have developed a computer-aided diagnosis (CAD) method to aid in the clinical diagnosis of Alzheimer's disease (AD). The method, called DMA-HPCNet, utilizes a lightweight dual multi-level hybrid pyramid convolutional neural network to analyze magnetic resonance imaging (MRI) scans of AD patients. The researchers found that the DMA-HPCNet model performed efficiently in AD-related classification tasks with low computational cost. This research provides a potential tool for improving the diagnosis of AD using machine learning techniques. [Extracted from the article]