Results 81 to 90 of about 3,606,574 (279)
$L^2$ Asymptotics for High-Dimensional Data [PDF]
We develop an asymptotic theory for $L^2$ norms of sample mean vectors of high-dimensional data. An invariance principle for the $L^2$ norms is derived under conditions that involve a delicate interplay between the dimension $p$, the sample size $n$ and ...
Wu, Wei Biao, Xu, Mengyu, Zhang, Danna
core
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker +16 more
wiley +1 more source
Screening for lung cancer: A systematic review of overdiagnosis and its implications
Low‐dose computed tomography (CT) screening for lung cancer may increase overdiagnosis compared to no screening, though the risk is likely low versus chest X‐ray. Our review of 8 trials (84 660 participants) shows added costs. Further research with strict adherence to modern nodule management strategies may help determine the extent to which ...
Fiorella Karina Fernández‐Sáenz +12 more
wiley +1 more source
Design of high dimensional data acquisition system of industrial field
For problem of high-speed data acquisition and transmission of high dimensional spectral data of industrial field, the paper proposed a design scheme of high dimensional data acquisition system. The system selects TMS320C6713B DSP chip as core processing
ZHAO An-xin, ZHANG Cai-tian
doaj +1 more source
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
Modern applications increasingly involve high-dimensional and heterogeneous data, e.g., datasets formed by combining numerous measurements from myriad sources.
Balzano, Laura +2 more
core
High dimensional data clustering
Clustering becomes difficult due to the increasing sparsity of such data, as well as the increasing difficulty in distinguishing distances between data points. The proposed method called “kernel trick” and “Collective Neighbour Clustering”, which takes as input measures of correspondence between pairs of data points.
M. Pavithra, R.M.S. Parvathi
openaire +1 more source
Cytoplasmic p21 promotes stemness of colon cancer cells via activation of the NFκB pathway
Cytoplasmic p21 promotes colorectal cancer stem cell (CSC) features by destabilizing the NFκB–IκB complex, activating NFκB signaling, and upregulating BCL‐xL and COX2. In contrast to nuclear p21, cytoplasmic p21 enhances spheroid formation and stemness transcription factor CD133.
Arnatchai Maiuthed +10 more
wiley +1 more source
Analyzing high dimensional correlated data using feature ranking and classifiers
The Illumina Infinium HumanMethylation27 (Illumina 27K) BeadChip assay is a relatively recent high-throughput technology that allows over 27,000 CpGs to be assayed.
Patil Abhijeet R +3 more
doaj +1 more source
A rough set based subspace clustering technique for high dimensional data
Subspace clustering aims at identifying subspaces for cluster formation so that the data is categorized in different perspectives. The conventional subspace clustering algorithms explore dense clusters in all the possible subspaces.
B. Jaya Lakshmi, M. Shashi, K.B. Madhuri
doaj +1 more source
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié +13 more
wiley +1 more source

