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Conv-ERVFL: Convolutional Neural Network Based Ensemble RVFL Classifier for Alzheimer's Disease Diagnosis
journal contribution
posted on 2023-02-14, 04:34 authored by R Sharma, T Goel, M Tanveer, PN Suganthan, Imran RazzakImran Razzak, R MuruganAs per the latest statistics, Alzheimer's disease (AD) has become a global burden over the following decades. Identifying AD at the intermediate stage became challenging, with mild cognitive impairment (MCI) utilizing credible biomarkers and robust learning approaches. Neuroimaging techniques like magnetic resonance imaging (MRI) and positron emission tomography (PET) are practical research approaches that provide structural atrophies and metabolic variations. With the help of MRI and PET scans, metabolic and structural changes in AD patients can be visible even ten years before the disease's onset. This paper proposes a novel wavelet packet transform-based structural and metabolic image fusion approach using MRI and PET scans. An eight-layer trained CNN extracts features from multiple layers and these features are fed to an ensemble of non-iterative random vector functional link (RVFL) models. The RVFL network incorporates the $s$-membership fuzzy function as an activation function that helps overcome outliers. Lastly, outputs of all the customized RVFL classifiers are averaged and fed to the RVFL classifier to make the final decision. Experiments are performed over Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and classification is made over CN vs. AD vs. MCI. The model performance obtained is decent enough to prove the effectiveness of the fusion-based ensemble approach.
History
Journal
IEEE Journal of Biomedical and Health InformaticsVolume
PPPagination
1-9Location
United StatesPublisher DOI
ISSN
2168-2194eISSN
2168-2208Language
engPublication classification
C1.1 Refereed article in a scholarly journalIssue
99Publisher
Institute of Electrical and Electronics Engineers (IEEE)Usage metrics
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No categories selectedKeywords
AgingBrain DisordersBiomedical ImagingNeurodegenerativeNeurosciencesAcquired Cognitive ImpairmentDementiaAlzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD)Alzheimer's Disease2.1 Biological and endogenous factors2 Aetiology4 Detection, screening and diagnosis4.1 Discovery and preclinical testing of markers and technologiesNeurological
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