Results 61 to 70 of about 2,151 (154)

Nonnegative Matrix Factorization (NMF) with Heteroscedastic Uncertainties and Missing data

, 2016
Vectorized update rules for NMF with heteroscedastic measurements and the proof. The code NonnegMFPy is available at https://github.com/guangtunbenzhu/NonnegMFPy and can be installed through PyPI.
openaire   +2 more sources

High ALG1 Expression Is Correlated With Poor Prognosis and the Immune Microenvironment in Glioma

Journal of Cellular and Molecular Medicine, Volume 30, Issue 8, April 2026.
ABSTRACT Glioma is the most prevalent primary tumour in the central nervous system. This study investigates ALG1 expression in glioma and its clinical significance. Using the TCGA and CGGA databases, a bioinformatics analysis examines ALG1 expression, its prognostic value, and its link to the immune microenvironment. Clinical samples are analysed using
Shuxiang Li, Yang Xia, Qiang Liu, Xin Qian, Anhong Liu, Jia Wang, Xinyu Wang, Di Zuo, Jing Zhang, Jinhai Ma, Peng Gao   +10 more
wiley   +1 more source

Proteogenomic Characterization Reveals Subtype‐Specific Therapeutic Potential for HER2‐Low Breast Cancer

Advanced Science, Volume 13, Issue 12, 27 February 2026.
Multiomic profiling of HER2‐low breast cancer identifies three proteomic subtypes with distinct therapeutic strategies: endocrine, antiangiogenic, and anti‐HER2 therapies. Genomic and lactate modification landscapes are detailed, providing insights for precise management.
Shouping Xu, Keda Yu, Lei Liu, Qin Wang, Xiaohui Wu, Yihai Chen, Guozheng Li, Xin Zhang, Bo Wei, Zitong Fu, Abiyasi Nanding, Zuxianglan Zhao, Lingbing Yang, Xingda Zhang, Jianyu Wang, Wantong Sun, Yi Hao, Zhongyi Cheng, Xiaojiang Cui, Hao Wu, Da Pang   +20 more
wiley   +1 more source

AI‐enhanced Centiloid quantification of amyloid PET images

Alzheimer's &Dementia, Volume 22, Issue 2, February 2026.
Abstract INTRODUCTION The Centiloid scale is the standard for amyloid (Aβ) PET quantification in research and clinical settings. However, variability between tracers and scanners remains a challenge. METHODS This study introduces DeepSUVR, a deep learning method to correct Centiloid quantification, by penalizing implausible longitudinal trajectories ...
Pierrick Bourgeat, Jurgen Fripp, Leo Lebrat, Ying Xia, Azadeh Feizpour, Timothy Cox, Georgios Zisis, Ashley Gillman, Manu S. Goyal, Duygu Tosun, Tammie LS. Benzinger, Pamela LaMontagne, Michael Breakspear, Michelle K. Lupton, Cathy Short, Robert Adam, Joanne S. Robertson, Reisa Sperling, Sid E. O'Bryant, Sterling C. Johnson, Clifford R. Jack Jr, Christopher G. Schwarz, Frederik Barkhof, Gill Farrar, Ariane Bollack, Lyduine E. Collij, Susan Landau, Robert Koeppe, for the Alzheimer's Disease Neuroimaging Initiative, OASIS3, the A4/LEARN Study Team, the AMYPAD consortium, The Health and Aging Brain Study (HABS‐HD) Study Team, Mayo Clinic Study of Aging, WRAP, ADNI‐DOD, PISA, ADNeT, the AIBL research group, John C. Morris, Michael W. Weiner, Victor L. Villemagne, Colin L. Masters, Christopher C. Rowe, Vincent Dore   +44 more
wiley   +1 more source

Regularized nonnegative matrix factorization: Geometrical interpretation and application to spectral unmixing

International Journal of Applied Mathematics and Computer Science, 2014
Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique.
Zdunek Rafał
doaj   +1 more source

Sophisticated Audio Source Separation: A Statistical Exploration of Clarity and Precision With FastICA

Engineering Reports, Volume 8, Issue 1, January 2026.
This workflow presents a complete pipeline for audio data processing, beginning with format conversion, channel adjustments, and cleaning, followed by enhancement and visualization techniques. It further applies signal separation using FastICA, postprocessing, and evaluation metrics (SDR, SIR, SAR) to improve audio analysis and support future research ...
Md. Razu Ahmed, Jannatul Mauya, Md. Shamim Reza, Ruhul Amin   +3 more
wiley   +1 more source

Similarity Learning-Induced Symmetric Nonnegative Matrix Factorization for Image Clustering

IEEE Access, 2019
As a typical variation of nonnegative matrix factorization (NMF), symmetric NMF (SNMF) is capable of exploiting information of the cluster embedded in the matrix of similarity.
Wei Yan, Bob Zhang, Zuyuan Yang, Shengli Xie   +3 more
doaj   +1 more source

Underwater acoustic target signal enhancement algorithm optimized by feature preservation and noise update [PDF]

Zhihui kongzhi yu fangzhen
The enhancement effect of the classic Nonnegative Matrix Factorization (NMF) applied to underwater acoustic target signal is unsatisfactory for the feature overlap of underwater acoustic target signal and the variability of ocean underwater acoustic ...
XIAO Haixia, CUI Shuangyue, LI Dawei, SUN Mingming, LIU Xianzhong, YANG Zhenxin
doaj   +1 more source

Novel methods for spatial risks analysis and quantitative source apportionment of heavy metals pollution in agricultural soils

Journal of Agriculture and Food Research
Precision pollution control relies on accurate spatial interpolation and quantitative source apportionment. This study addresses key methodological gaps by developing two novel tools: a non-negative constrained biharmonic spline interpolation algorithm ...
Qinqin Yu, Jinying Li, Jiahao Li, Tong Liu, Fangyuan Chen, Yao Liu, Haoming Wang, Shaoyang Tao, Min Zhou, Haobo Hou   +9 more
doaj   +1 more source

Nonnegative Matrix Factorization of time frequency representation of vibration signal for local damage detection – comparison of algorithms

E3S Web of Conferences, 2018
Local damage detection in rotating machine elements is very important problem widely researched in the literature. One of the most common approaches is the vibration signal analysis.
Wodecki Jacek
doaj   +1 more source