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Brain fiber structure estimation based on principal component analysis and RINLM filter
Diffusion magnetic resonance imaging is a technique for non-invasive detection of microstructure in the white matter of the human brain, which is...
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Principal Component Analysis of Grasp Force and Pose During In-Hand Manipulation
PurposeThe manner in which healthy humans interact with objects as they move them within the hand is essential for activities of everyday life. The...
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Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer’s from mixed Alzheimer’s disease
Alzheimer’s disease (AD) is often mixed with cerebrovascular disease (AD-CVD). Heterogeneity of dementia etiology and the overlap** of...
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Extraction and Digitization of ECG Signals from Standard Clinical Portable Document Format Files for the Principal Component Analysis of T-wave Morphology
Introduction: T-wave analysis from standard electrocardiogram (ECG) remains one of the most available clinical and research methods for evaluating...
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Tracking the Reliability of Force Plate-Derived Countermovement Jump Metrics Over Time in Female Basketball Athletes: A Comparison of Principal Component Analysis vs. Conventional Methods
BackgroundEstablishing the reliability of countermovement jump (CMJ) metrics over multiple weeks can be important in understanding and tracking...
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Sparse principal component analysis based on genome network for correcting cell type heterogeneity in epigenome-wide association studies
In epigenome-wide association studies (EWAS), the mixed methylation expression caused by the combination of different cell types may lead the...
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Iterative principal component analysis method for improvised classification of breast cancer disease using blood sample analysis
Breast cancer is the most common cancer in women occurring worldwide. Some of the procedures used to diagnose breast cancer are mammogram, breast...
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Quantification of Compatibility Between Polymeric Excipients and Atenolol Using Principal Component Analysis and Hierarchical Cluster Analysis
An important challenge to overcome in the solid dosage forms technology is the selection of the most biopharmaceutically efficient polymeric...
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Image-based cell subpopulation identification through automated cell tracking, principal component analysis, and partitioning around medoids clustering
In vitro cell culture model systems often employ monocultures, despite the fact that cells generally exist in a diverse, heterogeneous...
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Investigating the Impact of Gastric Emptying on Pharmacokinetic Parameters Using Delay Differential Equations and Principal Component Analysis
Background and ObjectivesLosartan presents multiple peaks after single oral administration, which can be attributed to gastric emptying. The aim of...
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Lymphocyte–monocyte–neutrophil index: a predictor of severity of coronavirus disease 2019 patients produced by sparse principal component analysis
BackgroundIt is important to recognize the coronavirus disease 2019 (COVID-19) patients in severe conditions from moderate ones, thus more effective...
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Altered functional brain networks in coronary heart disease: independent component analysis and graph theoretical analysis
Coronary heart disease (CHD) confers a high risk of cognitive and mental impairments in patients. This study aimed to explore the association of CHD...
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Dimensionality reduction beyond neural subspaces with slice tensor component analysis
Recent work has argued that large-scale neural recordings are often well described by patterns of coactivation across neurons. Yet the view that...
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The metabolic spatial covariance pattern of definite idiopathic normal pressure hydrocephalus: an FDG PET study with principal components analysis
Identification of patients with idiopathic normal pressure hydrocephalus (iNPH) in a collective with suspected neurodegenerative disease is...
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Screening of Bioequivalent Extended-Release Formulations for Metformin by Principal Component Analysis and Convolution-Based IVIVC Approach
Bioequivalence (BE) is usually hard to achieve for extended-release (ER) dosage form products due to not only its complicated formulation but also to...
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A mediation analysis framework based on variance component to remove genetic confounding effect
Identification of pleiotropy at the single nucleotide polymorphism (SNP) level provides valuable insights into shared genetic signals among...
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SMART (Splitting-Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks
Functional networks (FNs) hold significant promise in understanding brain function. Independent component analysis (ICA) has been applied in...
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Improved robust tensor principal component analysis for accelerating dynamic MR imaging reconstruction
Dynamic magnetic resonance imaging (dMRI) strikes a balance between reconstruction speed and image accuracy in medical imaging field. In this paper,...
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Biologically plausible single-layer networks for nonnegative independent component analysis
An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind...
