Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features
Journal
Journal of the Formosan Medical Association
Date Issued
2023-12-02
Author(s)
Huang, Yu-Hua
Chen, Yi-Chun
Ho, Wei-Min
Lee, Ren-Guey
Chung, Ren-Hua
Liu, Yu-Li
Chang, Pi-Yueh
Chang, Shih-Cheng
Wang, Chaung-Wei
Chung, Wen-Hung
Tsai, Shih-Jen
Lee, Yun-Shien
Hsiao, Chun-Chieh
Abstract
Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.
Subjects
Alzheimer's disease; Artificial neural networks (ANNs); Machine learning; Single nucleotide polymorphisms; Whole-genome genotyping; Whole-genome sequencing
SDGs
Publisher
Elsevier B.V.
Type
journal article