id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
brainmatters-1063	Iqbal, Rayyan	The Potential of Hybrid Models in Alzheimer's Diagnosis: Combining Neural Networks and SVMs for Enhanced Accuracy 	2025	6	.pdf	application/pdf	2850	164	47	In one study using a dataset of healthy individuals, those with early Alzheimer’s, and those with late-stage Alzheimer’s, a CNN model called ResNet-18 achieved an impressive 96.85% accuracy in distinguishing between different stages of the disease based on MRI and PET scans (Odusami et al., 2021). Hybrid Models: Combining Neural Networks and SVMs for Enhanced Accuracy In recent years, hybrid models that combine convolutional neural networks (CNNs) and support vector machines (SVMs) have gained attention in Alzheimer’s disease diagnosis, offering a more comprehensive approach to early detection and classification (Li 2023).	cache/brainmatters-1063.pdf	txt/brainmatters-1063.txt