Comparative study of detection and classification of Alzheimer's disease using Hybrid model and CNN
C R Nagarathna, M. Kusuma
Abstract
From the past decade, the researcher makes use of deep learning techniques for their research. The objective of various applications is achieved using these techniques. Alzheimer's is a physical brain disease, recently much research is going on to develop an efficient model to diagnose the early stages of Alzheimer's. The deep learning technique in the medical field helps to find medicines and diagnosis of disease. In this paper, we experimented Hybrid model, which is a combination of VGG19 and additional layers, and a CNN deep learning model for detecting and classifying the different stages of Alzheimer's. and compare their performance it shows that the Hybrid model works efficiently in detecting and classifying the different stages of Alzheimer's. We Analyzed the model for the Magnetic resonance imaging dataset