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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: 2021-01-26 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 連結: http://doi.org/10.1109/TAAI48200.2019.8959854
    DOI: 10.1109/TAAI48200.2019.8959854
    顯示於類別:[資訊科學系] 會議論文

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