Results 51 to 60 of about 564,038 (269)
Intravitreal GD2‐Specific Chimeric Antigen Receptor T‐Cell Therapy for Refractory Retinoblastoma
Pediatric Blood &Cancer, EarlyView.ABSTRACT Effective treatments for advanced, treatment‐resistant retinoblastoma (RB) remain limited. GD2‐specific chimeric antigen receptor (CAR) T cells show potent antitumor activity with minimal toxicity but have not previously been evaluated in RB.
Subongkoch Subhadhirasakul +13 more
wiley +1 more source
IEEE Access, 2018 The spectral unmixing technique is an effective method of solving the mixed pixel problem in the hyperspectral remote sensed imagery. During the process, endmember extraction algorithm (EEA) is significant for the creation of material abundance maps ...
Ke Wu +3 more
doaj +1 more source
Cancer Informatics, 2022 Identifying individual mechanisms involved in complex diseases, such as cancer, is essential for precision medicine. Their characterization is particularly challenging due to the unknown relationships of high-dimensional omics data and their inter ...
Sarah-Laure Rincourt +2 more
doaj +1 more source
Scalable Group Level Probabilistic Sparse Factor Analysis
, 2016 Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation.
Eriksen, Casper T. +8 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Gastrointestinal graft‐versus‐host disease (GI GVHD) following hematopoietic stem cell transplant is typically managed with medical therapy, but surgery and angioembolization may be warranted in selected cases with life‐threatening complications.
Gaia Brunetti +12 more
wiley +1 more source
Face Recognition Based on Robust Principal Component Analysis and Kernel Sparse Representation [PDF]
Jisuanji gongcheng, 2016 Aiming at the problems that the existing face recognition methods are hard to efficiently overcome the effect of noise and error disturbance (such as illumination,occlusion,and face expression).Kernel sparse representation classification based on Robust ...
LIAO Ruihua,LI Yongfan,LIU Hong
doaj +1 more source
Online Tensor Robust Principal Component Analysis
IEEE Access, 2022 Online robust principal component analysis (RPCA) algorithms recursively decompose incoming data into low-rank and sparse components. However, they operate on data vectors and cannot directly be applied to higher-order data arrays (e.g. video frames). In
Mohammad M. Salut, David V. Anderson
doaj +1 more source
Biobjective sparse principal component analysis
Journal of Multivariate Analysis, 2014 Principal Components are usually hard to interpret. Sparseness is considered as one way to improve interpretability, and thus a trade-off between variance explained by the components and sparseness is frequently sought. In this note we address the problem of simultaneous maximization of variance explained and sparseness, and a heuristic method is ...
Carrizosa Priego, Emilio José +1 more
openaire +3 more sources
Sparse multivariate functional principal component analysis
Stat, 2022 We introduce a sparse multivariate functional principal component analysis method by incorporating ideas from the group sparse maximum variance method to multivariate functional data. Our method can avoid the “curse of dimensionality” from a high‐dimensional dataset and enjoy interpretability at the same time. In particular, our unsupervised method can
Jun Song, Kyongwon Kim
openaire +2 more sources
Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source