Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography

Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography

Abstract Background The progression of Alzheimer’s dementia (AD) can be classified into three stages: cognitive unimpairment (CU), mild cognitive impairment (MCI), and AD. The purpose of this study was to implement a machine learning (ML) framework for AD stage classification using the standard upta...

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Bibliographic Details
Main Authors: Sang Won Park, Na Young Yeo, Jinsu Lee, Suk-Hee Lee, Junghyun Byun, Dong Young Park, Sujin Yum, Jung-Kyeom Kim, Gihwan Byeon, Yeshin Kim, Jae-Won Jang, for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: BMC 2023-04-01
Series:BioMedical Engineering OnLine
Subjects:
Alzheimer's disease
Cognitive dysfunction
Positron-emission tomography
Tau proteins
Machine learning
Online Access:https://doi.org/10.1186/s12938-023-01107-w

Internet

https://doi.org/10.1186/s12938-023-01107-w

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