Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration-Reference-Cited by-同舟云学术

Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration

Published:2015-07-14 Issue:4 Volume:71 Page:918-928
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Chen Tianle¹,Zeng Donglin²,Wang Yuanjia³

Affiliation:

1. Biogen; Cambridge, MA 02142 USA

2. Department of Biostatistics; University of North Carolina at Chapel Hill; Chapel Hill, NC 27599 USA

3. Department of Biostatistics, Mailman School of Public Health; Columbia University; New York, NY 10032 USA

Funder

National Institute of Neurological Disorders and Stroke

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12343/fullpdf

Reference21 articles.

1. Apoe genotype effects on alzheimers disease onset and epidemiology;Ashford;Journal of Molecular Neuroscience,2004

2. Bach , F. R. Lanckriet , G. R. G. 2004 Multiple kernel learning, conic duality, and the smo algorithm

3. Daemen , A. Moor , B. D. 2009 Development of a kernel function for clinical data 5913 5917

4. Combining early markers strongly predicts conversion from mild cognitive impairment to Alzheimer's disease;Devanand;Biological Psychiatry,2008

5. Diggle , P. Heagerty , P. Liang , K.-Y. Zeger , S. 2002

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comprehensive overview of Alzheimer's disease utilizing Machine Learning approaches;Multimedia Tools and Applications;2024-06-11

2. Effectiveness of Mental Health Care by Using Machine Learning on Manufacturing Worker;International Journal of Precision Engineering and Manufacturing-Smart Technology;2023-07-01

3. Deep learning for clinical decision-making and improved healthcare outcome;Deep Learning in Personalized Healthcare and Decision Support;2023

4. Prediction of high and low disease activity in early MS patients using multiple kernel learning identifies importance of lateral ventricle intensity;Multiple Sclerosis Journal - Experimental, Translational and Clinical;2022-07

5. Predicting conversion from mild cognitive impairment to Alzheimer’s disease with multimodal latent factors;Journal of Clinical and Experimental Neuropsychology;2022-04-21