Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning
Journal
Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
Date Issued
2019
Author(s)
Abstract
This paper presents machine learning based framework to the analysis and modeling of several neurodegenerative diseases by using features from blood-based biomarkers. The proposed approaches can be employed for early detection of Alzheimer's disease (AD) or Parkinson's disease (PD). In particular, we applied LDA (linear discriminant analysis) for visualizing the dataset as 2D or 3D scatter plots. Moreover, we constructed various classifiers for several different tasks of classification, and explore the accuracy of these classifiers. Based on our experiments, random forests are in general a very good choice of these tasks considering both the computing time (during modeling and prediction) and the accuracy. © 2019 IEEE.
Event(s)
24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
Subjects
Biomarkers; Classification; Linear discriminant analysis; Multivariate imputation by chained equations; Neurodegenerative disease
SDGs
Other Subjects
Biomarkers; Blood; Classification (of information); Decision trees; Discriminant analysis; Machine learning; Multivariant analysis; Alzheimer's disease; Analysis and modeling; Computing time; Linear discriminant analysis; Modeling and predictions; Multivariate imputation by chained equations; Parkinson's disease; Scatter plots; Neurodegenerative diseases
Publisher
Institute of Electrical and Electronics Engineers Inc.
Type
conference paper