id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-5634	R. Arumugam, A. Murugan	A Comprehensive Evaluation of Deep Learning Architectures and Traditional Machine Learning Algorithms for Prognostic Modeling in Alzheimer’s disease	2025	9	.pdf	application/pdf	3893	242	55	On the other hand, deep learning models such as deep neural networks (DNNs) can automatically learn useful patterns from data, and when trained properly, they often give better results. This study compares both traditional ML and deep learning models for predicting Alzheimer’s Disease using the OASIS cross-sectional dataset.	cache/cana-5634.pdf	txt/cana-5634.txt