Results 41 to 50 of about 150,011 (287)

Independent Component Analysis for Magnetic Resonance Image Analysis

EURASIP Journal on Advances in Signal Processing, 2008
Independent component analysis (ICA) has recently received considerable interest in applications of magnetic resonance (MR) image analysis. However, unlike its applications to functional magnetic resonance imaging (fMRI) where the number ...
San-Kan Lee, Ching-Wen Yang, Sek-Kwong Poon, Clayton Chi-Chang Chen, Cheng-Chieh Chen, Jyh-Wen Chai, Hsian-Min Chen, Yen-Chieh Ouyang   +7 more
doaj   +1 more source

Parallel group independent component analysis for massive fMRI data sets. [PDF]

PLoS ONE, 2017
Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation.
Shaojie Chen, Lei Huang, Huitong Qiu, Mary Beth Nebel, Stewart H Mostofsky, James J Pekar, Martin A Lindquist, Ani Eloyan, Brian S Caffo   +8 more
doaj   +1 more source

Targeting the ARRDC3–DRP1 Axis via hUMSC‐Derived Exosomal CRYAB for Neuroprotection in Cerebral Ischemia/Reperfusion Injury

Advanced Healthcare Materials, EarlyView.
Intranasally administered hUMSC‐derived exosomes modulate the CRYAB–ARRDC3–Drp1 axis, alleviating mitochondrial dysfunction and ferroptosis, enhancing neuronal survival, reducing oxidative stress, and promoting functional recovery in ischemia‐reperfusion injury, offering a promising therapeutic strategy for ischemic stroke.
Rong ji, Zengyu Zhang, Zhuohang Liu, Kaicheng Yang, Xueyu Mao, Min Chu, Yong Wang, Jing Zhao   +7 more
wiley   +1 more source

A review of independent component analysis application to microarray gene expression data

BioTechniques, 2008
Independent component analysis (ICA) methods have received growing attention as effective data-mining tools for microarray gene expression data. As a technique of higher-order statistical analysis, ICA is capable of extracting biologically relevant gene ...
Wei Kong, Charles R. Vanderburg, Hiromi Gunshin, Jack T. Rogers, Xudong Huang   +4 more
doaj   +1 more source

Factor analysis of financial time series using EEMD-ICA based approach

Sustainable Futures, 2020
Analyses of financial time series and exploring its underlying characteristic factors are longstanding research problems. Ensemble empirical mode decomposition (EEMD) and independent component analysis (ICA) are two methods developed to deal with these ...
Lu Xian, Kaijian He, Chao Wang, Kin Keung Lai   +3 more
doaj   +1 more source

Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction

Advanced Healthcare Materials, EarlyView.
Atherosclerosis management is hindered by poor drug targeting and plaque heterogeneity. Nanotechnology overcomes these barriers via three core strategies: (1) target‐engineered nanocarriers that achieve lesion‐specific precision via ligand modification, biomimetic camouflage, stimuli‐responsive release, and self‐propelling nanomotors; (2) catalytic ...
Yuqi Yang, Jingguo Qu, Tonghuan Xiao, Xinyang Han, Michael Tin‐Cheung Ying   +4 more
wiley   +1 more source

Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices

Frontiers in Human Neuroscience, 2012
Parallel Independent Component Analysis (para-ICA) is a multivariate method that can identify complex relationships between different data modalities by simultaneously performing Independent Component Analysis on each data set while finding mutual ...
Timothy eMeier, Joseph eWildenberg, Joseph eWildenberg, Jingyu eLiu, Jingyu eLiu, Jiayu eChen, Jiayu eChen, Vince eCalhoun, Vince eCalhoun, Bharat eBiswal, Mary eMeyerand, Mary eMeyerand, Mary eMeyerand, Rasmus eBirn, Rasmus eBirn, Rasmus eBirn, Vivek ePrabhakaran, Vivek ePrabhakaran, Vivek ePrabhakaran, Vivek ePrabhakaran   +19 more
doaj   +1 more source

Independent component analysis for brain FMRI does indeed select for maximal independence. [PDF]

PLoS ONE, 2013
A recent paper by Daubechies et al. claims that two independent component analysis (ICA) algorithms, Infomax and FastICA, which are widely used for functional magnetic resonance imaging (fMRI) analysis, select for sparsity rather than independence.
Vince D Calhoun, Vamsi K Potluru, Ronald Phlypo, Rogers F Silva, Barak A Pearlmutter, Arvind Caprihan, Sergey M Plis, Tülay Adalı   +7 more
doaj   +1 more source

Indole‐3‐Propionic Acid Improves Alveolar Development Impairment via Targeting VAMP8‐mediated SNAREs Complex Formation in Bronchopulmonary Dysplasia

Advanced Science, EarlyView.
This study aims to evaluate the impact of the tryptophan‐derived metabolite indole‐3‐propionic acid (IPA) on lung development and autophagic flux. IPA alleviates hyperoxia‐induced alveolar arrest by promoting autophagosome‐lysosome fusion via inhibition of VAMP8 phosphorylation, which is suggestive of a promising therapeutic target of BPD.
Beibei Wang, Xu Chen, Haowei Xu, Zhiqi Zeng, Keyu Lu, Yu Mao, Qianru Lv, Hui Shi, Song Liu, Xian Shen, Chunyu Yin, Yang Yang, Yan Guo, Xingyun Wang, Rui Cheng   +14 more
wiley   +1 more source

Comparing patterns of component loadings: Principal Component Analysis (PCA) versus Independent Component Analysis (ICA) in analyzing multivariate non-normal data [PDF]

Behavior Research Methods, 2012
Principal component analysis identifies uncorrelated components from correlated variables, and a few of these uncorrelated components usually account for most of the information in the input variables. Researchers interpret each component as a separate entity representing a latent trait or profile in a population. However, the components are guaranteed
Donghoh, Kim, Se-Kang, Kim
openaire   +2 more sources