Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning

被引：1

作者：

Chiu, Shu-I ^{[1
]}

Chen, Ta-Fu ^{[2
]}

Lin, Chin-Hsien ^{[2
]}

Jang, Jyh-Shing Roger ^{[1
]}

Lim, Wee Shin ^{[1
]}

Chiu, Ming-Jang ^{[2
]}

机构：

[1] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[2] Natl Taiwan Univ, Natl Taiwan Univ Hosp, Coll Med, Dept Neurol, Taipei, Taiwan

来源：

2019 INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI) | 2019年

关键词：

Linear discriminant analysis; Classification; Multivariate imputation by chained equations; Neurodegenerative disease; Biomarkers; MILD COGNITIVE IMPAIRMENT; ALZHEIMERS; CLASSIFICATION; ALGORITHMS; DIAGNOSIS;

D O I：

10.1109/taai48200.2019.8959854

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

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.

引用

页数：6

共 38 条

[1]

Ahmed M. R., 2018, PROSPECTS IEEE REV B, V12, P19, DOI DOI 10.1109/RBME.2018.2886237

[2]

[Anonymous], 2008, INFORM SCI STAT

[3] SmcHD1, containing a structural-maintenance-of-chromosomes hinge domain, has a critical role in X inactivation [J].

Blewitt, Marnie E. ;

Gendrel, Anne-Valerie ;

Pang, Zhenyi ;

Sparrow, Duncan B. ;

Whitelaw, Nadia ;

Craig, Jeffrey M. ;

Apedaile, Anwyn ;

Hilton, Douglas J. ;

Dunwoodie, Sally L. ;

Brockdorff, Neil ;

Kay, Graham F. ;

Whitelaw, Emma .

NATURE GENETICS, 2008, 40 (05) :663-669

[4] Random forests [J].

Breiman, L .

MACHINE LEARNING, 2001, 45 (01) :5-32

[5]

Buuren S. V., J STAT SOFTWARE, P1

[6]

Chang C. C., 2017, P 11 INT C UB INF MA, P57, DOI DOI 10.1145/3022227.3022283

[7] New Assay for Old Markers-Plasma Beta Amyloid of Mild Cognitive Impairment and Alzheimer's Disease [J].

Chiu, M. J. ;

Yang, S. Y. ;

Chen, T. F. ;

Chieh, J. J. ;

Huang, T. Z. ;

Yip, P. K. ;

Yang, H. C. ;

Cheng, T. W. ;

Chen, Y. F. ;

Hua, M. S. ;

Horng, H. E. .

CURRENT ALZHEIMER RESEARCH, 2012, 9 (10) :1142-1148

[8]

Chiu M. J., J NEUROL NEUROSURG P, V88, P818

[9] Plasma tau as a window to the brainnegative associations with brain volume and memory function in mild cognitive impairment and early alzheimer's disease [J].

Chiu, Ming-Jang ;

Chen, Ya-Fang ;

Chen, Ta-Fu ;

Yang, Shieh-Yueh ;

Yang, Fan-Pei Gloria ;

Tseng, Tien-Wen ;

Chieh, Jen-Jie ;

Chen, Jia-Chun Rare ;

Tzen, Kai-Yuan ;

Hua, Mau-Sun ;

Horng, Herng-Er .

HUMAN BRAIN MAPPING, 2014, 35 (07) :3132-3142

[10] Combined Plasma Biomarkers for Diagnosing Mild Cognition Impairment and Alzheimer's Disease [J].

Chiu, Ming-Jang ;

Yang, Shieh-Yueh ;

Horng, Herni-Er ;

Yang, Che-Chuan ;

Chen, Ta-Fu ;

Chieh, Jen-Je ;

Chen, Hsin-Hsien ;

Chen, Ting-Chi ;

Ho, Chia-Shin ;

Chang, Shuo-Fen ;

Liu, Hao Chun ;

Hong, Chin-Yih ;

Yang, Hong-Chang .

ACS CHEMICAL NEUROSCIENCE, 2013, 4 (12) :1530-1536

← 1 2 3 4 →