The Role of Artificial Intelligence in Early Detection of Alzheimer’s Disease Through Neuroimaging

Abstract

Our elderly population faces Alzheimer’s disease (AD) as a neurodegenerative disorder that brings about memory issues beside cognitive deterioration until reaching total caregiver dependency. The successful intervention and slower disease progression requires prompt detection of Alzheimer's disease at an early stage. Traditional AD diagnostic methods depend on clinical evaluation and neuroimaging yet this double approach proves time-consuming and can confirm AD only after its later symptoms appear. Artificial intelligence tools emerged recently to improve early Alzheimer’s detection by processing MRI and PET neuroimaging results. The research evaluates how neural networks accomplish early Alzheimer's disease detection through examinations of brain imaging information. By enabling automatic medical image analysis through machines and ANN methods like CNNs and machine learning algorithms doctors can identify early signs of Alzheimer's disease before patients display clinical symptoms. Early detection through AI tools is analysed to better understand their medical transformative abilities as well as their diagnostic and therapeutic breakthroughs.