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Review Article |

Deep Learning Techniques for Early Detection of Alzheimer’s Disease: A Review

Author(s): V Sanjay1 and P Swarnalatha2

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 10, Issue 4, Special Issue on Complexity-BDA-ML

Publisher : FOREX Publication

Published : 30 October 2022

e-ISSN : 2347-470X

Page(s) : 899-905

DOI: https://doi.org/10.37391/IJEER.100425

Abstract

Alzheimer's disease (AD) is the most prevalent kind of dementia illness that can significantly impair a person's capability to carry out everyday tasks. According to findings, AD may be the third provoking reason of mortality among older adults, behind cancer and heart disease. Individuals at risk of acquiring AD must be identified before treatment strategies may be tested. The study's goal is to give a thorough examination of tissue structures using segmented MRI, which will lead to a more accurately labeling of certain brain illnesses. Several complicated segmentation approaches for identify AD have been developed. DL algorithms for brain structure segmentation and AD categorization have gotten a lot of attention since they can deliver accurate findings over a huge amount of data. As a result, DL approaches are increasingly favored over cutting-edge Machine Learning (ML) techniques. This study provides you with an overview of current trend deep learning-based segmentation algorithms for analyzing brain Magnetic Resonance Imaging for the treatment of AD. Finally, a conversation on the approaches' benefits and drawbacks, as well as future directives, was held, which may help researchers better comprehend present algorithms and methods in this field, and eventually design new and more successful algorithms.

Keywords: Alzheimer's disease (AD), ensemble computing, graph CNN, pulmonary, Adaboost and Neurocognitive.




V Sanjay, Research Scholar, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India; Email: sanjay.researcher@gmail.com

P Swarnalatha*, Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India; Email: pswarnalatha@vit.ac.in

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V Sanjay and P Swarnalatha (2022), Deep Learning Techniques for Early Detection of Alzheimer’s Disease: A Review. IJEER 10(4), 899-905. DOI: 10.37391/IJEER.100425.