Abstract
This paper proposes a parallel machine learning framework for detecting Alzheimer’s disease through T1-weighted MRI scans localised to the hippocampus, segmented between the left and right hippocampi. Feature extraction is first performed by 2 separately trained, unsupervised learning based AutoEncoders, where the left and right hippocampi are fed into their respective AutoEncoder. Classification is then performed by a pair of classifiers on the encoded data from the AutoEncoders, to which each pair of the classifiers are aggregated together using a soft voting ensemble process. The best averaged aggregated model results recorded was with the Gaussian Naïve Bayes classifier where sensitivity/specificity achieved were 80%/81% respectively and a balanced accuracy score of 80%.
Original language | English |
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Title of host publication | Brain Informatics |
Subtitle of host publication | 14th International Conference, BI 2021, Virtual Event, September 17–19, 2021, Proceedings |
Editors | Mufti Mahmud, M Shamim Kaiser, Stefano Vassanelli, Qionghai Dai, Ning Zhong |
Place of Publication | Cham |
Publisher | Springer, Cham |
Pages | 423-432 |
Number of pages | 10 |
Volume | 12960 |
Edition | 1st |
ISBN (Electronic) | 9783030869939 |
ISBN (Print) | 9783030869922 |
DOIs | |
Publication status | Published - 15 Sep 2021 |
Event | 14th International Conference on Brain Informatics: Innovation Computational Approaches for Understanding Brain Functions and Treat its Disorders - Virtual conference due to COVID-19, Padova - virtually, Italy Duration: 17 Sep 2021 → 19 Sep 2021 Conference number: 14 https://www.bi2021.org/ |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12960 LNCS/LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 14th International Conference on Brain Informatics |
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Abbreviated title | BI 2021 |
Country/Territory | Italy |
City | Padova - virtually |
Period | 17/09/21 → 19/09/21 |
Internet address |