Results 51 to 60 of about 2,306,590 (284)
Decomposable Principal Component Analysis
, 2008 We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation.
Hero III, Alfred O., Wiesel, Ami
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background and Aims Wilms tumour (WT) has excellent event‐free and overall survival (OS). However, small differences exist between countries participating in the same international study. This led us to examine variation in adherence to protocol recommendations as a potential contributing factor.
Suzanne Tugnait +23 more
wiley +1 more source
Principal Component Analysis in ECG Signal Processing
EURASIP Journal on Advances in Signal Processing, 2007 This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained.
Roig José Millet +4 more
doaj +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Arteriovenous malformations (AVMs) are rare, high‐flow, vascular anomalies that can occur either sporadically or as part of a genetic syndrome. AVMs can progress with serious morbidity and even mortality if left unchecked. Sirolimus is an mTOR inhibitor that is effective in low‐flow vascular malformations; however, its role in AVMs is unclear.
Will Swansson +3 more
wiley +1 more source
Geometrical Approximated Principal Component Analysis for Hyperspectral Image Analysis
Remote Sensing, 2020 Principal Component Analysis (PCA) is a method based on statistics and linear algebra techniques, used in hyperspectral satellite imagery for data dimensionality reduction required in order to speed up and increase the performance of subsequent ...
Alina L. Machidon +4 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Nurses are central to cancer care for children and adolescents, yet no comprehensive synthesis has defined essential core competencies for pediatric oncology nursing (PON) practice internationally, particularly in Latin America and the Caribbean (LAC).
Luís Carlos Lopes‐Júnior +7 more
wiley +1 more source
Low-Light Image Enhancement by Principal Component Analysis
IEEE Access, 2019 Under extreme low-lighting conditions, images have low contrast, low brightness, and high noise. In this paper, we propose a principal component analysis framework to enhance low-light-level images with decomposed luminance–chrominance components.
Steffi Agino Priyanka +2 more
doaj +1 more source
N-Dimensional Principal Component Analysis [PDF]
, 2010 In this paper, we first briefly introduce the multidimensional Principal Component Analysis (PCA) techniques, and then amend our previous N-dimensional PCA (ND-PCA) scheme by introducing multidirectional decomposition into ND-PCA implementation.
Yu, Hongchuan
core
Robust Principal Component Analysis on Graphs [PDF]
, 2015 Principal Component Analysis (PCA) is the most widely used tool for linear dimensionality reduction and clustering. Still it is highly sensitive to outliers and does not scale well with respect to the number of data samples.
Bresson, Xavier +4 more
core +2 more sources
Defining Roles in Pediatric Palliative Care: Perspectives From Oncology and Palliative Care Teams
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Early integration of pediatric palliative care (PPC) is associated with improved symptom management, quality of life, and healthcare utilization for children with cancer. Despite this, variation persists in how PPC is understood, operationalized, and integrated within pediatric oncology programs. In particular, ambiguity surrounding
Leeat Granek +13 more
wiley +1 more source