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Title: Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning
Authors: 邱淑怡
Chiu, Shu-i
Lin, Chin-Hsien
Lim, Wee Shin
Chiu, Ming-Jang
Contributors: 資科系
Keywords: Linear discriminant analysis;Classification;Multivariate imputation by chained equations;Neurodegenerative disease;Biomarkers
Date: 2019-11
Issue Date: 2021-01-26 15:16:20 (UTC+8)
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.
Relation: International Conference on Technologies and Applications of Artificial Intelligence, Taiwan, pp.1-6
Data Type: conference
DOI 連結:
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