Alzheimer disease (AD) is a progressive neurodegenerative disorder that impairs memory and cognitive function in older adults, placing a substantial burden on global healthcare systems. Early and accurate diagnosis is crucial for timely intervention, yet manual interpretation of magnetic resonance imaging (MRI) scans is often subjective, time-consuming, and prone to inter-observer variability and bias. To overcome these challenges, we propose NES-Net (Neuro-Synergy Network), a novel deep learning model for automated Alzheimer's detection from MRI data. NES-Net employs a multi-branch hybrid architecture that simultaneously captures structural, spatial, and semantic features of brain images. B... More >