EEG Signal Analysis Using Deep Learning Algorithms for Early Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is a challenging and progressive condition that impacts memory and cognitive function. Detecting it early can make a significant difference in treatment and quality of life. EEG, a non-invasive and cost-effective tool, offers a window into brain activity. In recent years, deep learning has revolutionized how we analyze complex biomedical signals like EEG. This article explores how modern AI techniques, particularly deep learning models such as CNNs and LSTMs, can help identify early signs of Alzheimer's disease through EEG analysis. We discuss EEG features, preprocessing steps, neural network architectures, and the future of intelligent diagnostics.

کلیدواژه ها:

Alzheimer's disease ، EEG analysis ، deep learning algorithms ، early diagnosis ، neural networks