Results 51 to 60 of about 14,660 (227)

Robust and sparse canonical correlation analysis based L(2,p)-norm

The Journal of Engineering, 2017
The objective function of canonical correlation analysis (CCA) is equivalent to minimising an L(2)-norm distance of the paired data. Owing to the characteristic of L(2)-norm, CCA is highly sensitive to noise and irrelevant features.
Zhong-rong Shi, Sheng Wang, Sheng Wang, Chuan-cai Liu   +3 more
doaj   +1 more source

Canonical Correlation Analysis (Cca) Algorithms For Multiple Data Sets: Application To Blind Simo Equalization

, 2005
Publication in the conference proceedings of EUSIPCO, Antalya, Turkey ...
Javier Vía, Ignacio Santamaría, Jesús Pérez 0001   +2 more
openaire   +3 more sources

Targeting Lactate‐Driven Stromal Autophagy via MCT1 Disrupts the Immunosuppressive Niche and Sensitizes Pancreatic Cancer to PD‐1 Blockade

Advanced Science, EarlyView.
Tumor‐derived lactate activates PSCs through MCT1‐mediated Vps34 lactylation and autophagy. These activated PSCs secrete CXCL9/10, upregulating PD‐1 on CD8+ T cells via the CXCR3/STAT3 axis to foster immunosuppression. Disrupting this metabolic crosstalk by targeting MCT1 effectively sensitizes pancreatic cancer to PD‐1 blockade, presenting a promising
Wenfeng Zhuo, Rong Hu, Yuhang Hu, Ping Hu, Shengbo Han, Guozheng Lv, Zhu Zeng, Yong Zhao, Yang Li, Yan Huang, Yingsong Zhao, Hongda Wang, Guangyu Zhao, Eryang Zhao, Gang Zhao   +14 more
wiley   +1 more source

Non-linear canonical correlation for joint analysis of MEG signals from two subjects

Frontiers in Neuroscience, 2013
We consider the problem of analysing magnetoencephalography (MEG) data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies.
Cristina eCampi, Cristina eCampi, Lauri Tapio Parkkonen, Riitta eHari, Aapo eHyvärinen, Aapo eHyvärinen   +5 more
doaj   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Seedling dynamics and community forecast for disturbed forests of the Western Himalayas: a multivariate analysis

Journal of Forest Science, 2020
The present study focuses on the forest structure of highly disturbed sites in Western Himalayan regions in Pakistan. In this study, the regeneration potential of conifer species is a key point for the assessment of future conifer status in disturbed ...
Afsheen Khan
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Permutation inference for canonical correlation analysis

NeuroImage, 2020
Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements.
Anderson M. Winkler, Olivier Renaud, Stephen M. Smith, Thomas E. Nichols   +3 more
doaj   +1 more source

A modified Canonical Correlation Analysis Method for SSVEP Frequency Recognition [PDF]

مجله مدل سازی در مهندسی, 2018
The canonical correlation analysis (CCA) is one of the most widely used frequency recognition methods in steady-state visual evoked potential (SSVEP)-based brain computer interface systems.
Sahar Sadeghi, Ali Maleki
doaj   +1 more source

Restricted kernel canonical correlation analysis

, 2012
Kernel canonical correlation analysis (KCCA) is a procedure for assessing the relationship between two sets of random variables when the classical method, canonical correlation analysis (CCA), fails because of the nonlinearity of the data.
Otopal, Nina
core   +1 more source