Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features.
Journal:
Journal of the Formosan Medical Association = Taiwan yi zhi
PMID:
38044212
Abstract
BACKGROUND: 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.
Authors
Keywords
Aged
Aged, 80 and over
Alzheimer Disease
Case-Control Studies
Female
Gene-Environment Interaction
Humans
Machine Learning
Male
Mitochondrial Precursor Protein Import Complex Proteins
Neural Networks, Computer
Polymorphism, Single Nucleotide
ROC Curve
Sensitivity and Specificity
Support Vector Machine