Revised Algorithm for Alzheimer Detection using DL Model and it’s Analysis

Computer Engineering

Alzheimer's disease (AD) presents a pressing challenge in modern healthcare due to its increasing presence in society and the need for early and accurate diagnosis in due course of time. This abstract exemplifies a novel and efficient method in utilising various techniques for the detection and classification of Alzheimer's disease through imaging data analysis.The proposed methodology involves the application of neural networks to also effectively understand various medical imaging parameters such as MRI and functional imaging data. These neural network architectures aim to automatically extract intricate patterns and features from brain images, enabling the identification of potential biomarkers and pattern impressions associated with Alzheimer's disease.This study uses an exhaustive comprehensive dataset which comprises imaging scans of individuals diagnosed with Alzheimer's disease and normal healthy brain.

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