Early Detection of Alzheimer’s Disease: An Extensive Review of Advancements in Machine Learning Mechanisms Using an Ensemble and Deep Learning Technique-Reference-Cited by-同舟云学术

Early Detection of Alzheimer’s Disease: An Extensive Review of Advancements in Machine Learning Mechanisms Using an Ensemble and Deep Learning Technique

Published:2023-12-11 Issue: Volume: Page:
ISSN:
Container-title:RAiSE-2023
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Author:

Neelakandan Renjith Prabhavathi¹^ORCID,Kandasamy Ramesh²^ORCID,Subbiyan Balasubramani³,Bennet Mariya Anto⁴

Affiliation:

1. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai 603103, Tamilnadu, India

2. Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore 641008, Tamilnadu, India

3. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522502, Andrapradesh, India

4. Department of Electronics and Communication Engineering, Vel Tech Rangaranjan Dr. Sagunthala R & D Institute of Science and Technology, Chennai 600062, Tamilnadu, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/10/pdf

Reference26 articles.

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2. Two-stage deep learning model for AD detection and prediction of the mild cognitive impairment time;Saleh;Neural Comp. Appl.,2022

3. AD Neuroimaging Initiative. Predicting the course of Alzheimer’s progression;Iddi;Brain Inform.,2019

4. Prediction of differentially expressed microRNAs in blood as potential biomarkers for AD by meta-analysis and adaptive boosting ensemble learning;Yuen;Alzheimer’s Res. Ther.,2021

5. Transfer learning using freeze features for Alzheimer neurological disorder detection using ADNI dataset;Naz;Multi. Syst.,2022

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