The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception
MW Weiner, DP Veitch, PS Aisen, LA Beckett… - Alzheimer's & …, 2013 - Elsevier
Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing,
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
2014 Update of the Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception
MW Weiner, DP Veitch, PS Aisen, LA Beckett… - Alzheimer's & …, 2015 - Elsevier
Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing,
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
Feature selection based on structured sparsity: A comprehensive study
Feature selection (FS) is an important component of many pattern recognition tasks. In these
tasks, one is often confronted with very high-dimensional data. FS algorithms are designed …
tasks, one is often confronted with very high-dimensional data. FS algorithms are designed …
Prediction of gene expression patterns with generalized linear regression model
Cell reprogramming has played important roles in medical science, such as tissue repair,
organ reconstruction, disease treatment, new drug development, and new species breeding …
organ reconstruction, disease treatment, new drug development, and new species breeding …
Brain imaging genomics: integrated analysis and machine learning
L Shen, PM Thompson - Proceedings of the IEEE, 2019 - ieeexplore.ieee.org
Brain imaging genomics is an emerging data science field, where integrated analysis of
brain imaging and genomics data, often combined with other biomarker, clinical, and …
brain imaging and genomics data, often combined with other biomarker, clinical, and …
Multi-view clustering and feature learning via structured sparsity
Combining information from various data sources has become an important research topic
in machine learning with many scientific applications. Most previous studies employ kernels …
in machine learning with many scientific applications. Most previous studies employ kernels …
Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers
Abstract The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI),
formally established in 2009, aims to provide resources and facilitate research related to …
formally established in 2009, aims to provide resources and facilitate research related to …
Feature selection via global redundancy minimization
Feature selection has been an important research topic in data mining, because the real
data sets often have high-dimensional features, such as the bioinformatics and text mining …
data sets often have high-dimensional features, such as the bioinformatics and text mining …
Structured sparsity regularized multiple kernel learning for Alzheimer's disease diagnosis
Multimodal data fusion has shown great advantages in uncovering information that could be
overlooked by using single modality. In this paper, we consider the integration of high …
overlooked by using single modality. In this paper, we consider the integration of high …
Genetics of the connectome
Connectome genetics attempts to discover how genetic factors affect brain connectivity.
Here we review a variety of genetic analysis methods—such as genome-wide association …
Here we review a variety of genetic analysis methods—such as genome-wide association …