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題名 Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning
作者 邱淑怡
Chiu, Shu-i
Lin, Chin-Hsien
Lim, Wee Shin
Chiu, Ming-Jang
貢獻者 資科系
關鍵詞 Linear discriminant analysis ; Classification ; Multivariate imputation by chained equations ; Neurodegenerative disease ; Biomarkers
日期 2019-11
上傳時間 26-Jan-2021 15:16:20 (UTC+8)
摘要 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.
關聯 International Conference on Technologies and Applications of Artificial Intelligence, Taiwan, pp.1-6
資料類型 conference
DOI http://doi.org/10.1109/TAAI48200.2019.8959854
dc.contributor 資科系
dc.creator (作者) 邱淑怡
dc.creator (作者) Chiu, Shu-i
dc.creator (作者) Lin, Chin-Hsien
dc.creator (作者) Lim, Wee Shin
dc.creator (作者) Chiu, Ming-Jang
dc.date (日期) 2019-11
dc.date.accessioned 26-Jan-2021 15:16:20 (UTC+8)-
dc.date.available 26-Jan-2021 15:16:20 (UTC+8)-
dc.date.issued (上傳時間) 26-Jan-2021 15:16:20 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/133775-
dc.description.abstract (摘要) 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.
dc.format.extent 324443 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) International Conference on Technologies and Applications of Artificial Intelligence, Taiwan, pp.1-6
dc.subject (關鍵詞) Linear discriminant analysis ; Classification ; Multivariate imputation by chained equations ; Neurodegenerative disease ; Biomarkers
dc.title (題名) Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning
dc.type (資料類型) conference
dc.identifier.doi (DOI) 10.1109/TAAI48200.2019.8959854
dc.doi.uri (DOI) http://doi.org/10.1109/TAAI48200.2019.8959854