چکیده مقاله
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
کلیدواژهها
نویسندگان
Anita Azizi Randi
Reyhaneh Jabbari
Reyhaneh Jabbari
Anita Azizi Rendi
شیوه ارجاع
Azizi Rendi, Anita and Jabbari, Reyhaneh,1404,EEG Signal Analysis Using Deep Learning Algorithms for Early Diagnosis of Alzheimer's Disease,11th International Conference on Interdisciplinary Researches in Electrical, Computer, Mechanical and Mechatronics Engineering in Iran and Islamic World,Tehran
ارائهشده در
مجموعه مقالات یازدهمین کنفرانس بین المللی تحقیقات بین رشته ای در مهندسی برق، کامپیوتر، مکانیک و مکاترونیک در ایران و جهان اسلام31 شهریور 1404 · تهران