Enhancing Security of Neurological Health Information Using Cryptography in Wireless Sensor Network

Volume 20 No 2 (2022)

Dr.R. Anurekha, N. Thirugnanasambandan , Dr.A. Rajivkannan

DOI: 10.14704/nq.2022.20.2.NQ22031

Abstract

Alzheimer's disease affects irreversible brain damage cells that control memory and reasoning. Owing to comparable brain patterns and pixel intensities, diagnosing Alzheimer's disease in elderly persons is challenging and necessitates a highly discriminative feature representation for classification. These representations can be learned from data using deep learning algorithms. To address these issues, previous research looks into the usefulness of rs-fMRI for multi-class classification of Alzheimer's disease and its phases, such as CN, SMC, EMCI, MCI, LMCI, and AD

Keywords

Alzheimer’s Disease, Motion Correction, Normalization, Multi Stage Classification, Security and Modified Advanced Encryption Standard

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