In this paper we explore the use of updated tensor decompositions for the monitoring of brain hemodynamics in neonates. For this study, we used concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, EEG, and brain oxygenation - measured using near-infrared spectroscopy. These measurements were obtained from 22 neonates undergoing an INSURE procedure (INtubation, SURfactant and Extubation) and sedation using propofol. To develop the monitoring framework using tensors, we used radial basis kernel function (RBF) to construct a similarity matrix for consecutive segments of the signals. These matrices were concatenated forming a tensor. Updating canonical polyadic decomposition was used to evaluate the impact of propofol in the coupling between the different signals. Results indicate, as previously reported, a drop in the interaction between signals due to propofol administration. This shows that tensor decompositions can be useful in order to monitor the coupling between different physiological signals.
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http://dx.doi.org/10.1109/EMBC.2019.8857846 | DOI Listing |
Quant Imaging Med Surg
January 2025
Henan Key Laboratory of Imaging and Intelligent Processing, Information Engineering University, Zhengzhou, China.
Background: Photon-counting computed tomography (CT) is an advanced imaging technique that enables multi-energy imaging from a single scan. However, the limited photon count assigned to narrow energy bins leads to increased quantum noise in the reconstructed spectral images. To address this issue, leveraging the prior information in the spectral images is essential.
View Article and Find Full Text PDFArtif Intell Med
February 2025
Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran. Electronic address:
Modeling Optical Coherence Tomography (OCT) images is crucial for numerous image processing applications and aids ophthalmologists in the early detection of macular abnormalities. Sparse representation-based models, particularly dictionary learning (DL), play a pivotal role in image modeling. Traditional DL methods often transform higher-order tensors into vectors and then aggregate them into a matrix, which overlooks the inherent multi-dimensional structure of the data.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Materials Science and Engineering, Kyoto University, Sakyo, Kyoto, 606-8501, Japan.
The discovery of novel materials is crucial for developing new functional materials. This study introduces a predictive model designed to forecast complex multi-component oxide compositions, leveraging data derived from simpler pseudo-binary systems. By applying tensor decomposition and machine learning techniques, we transformed pseudo-binary oxide compositions from the Inorganic Crystal Structure Database (ICSD) into tensor representations, capturing key chemical trends such as oxidation states and periodic positions.
View Article and Find Full Text PDFGenes (Basel)
November 2024
Department of Physics, Chuo University, Tokyo 112-8551, Japan.
Methionine is an essential amino acid. Dietary methionine restriction is associated with decreased tumor growth in preclinical studies and extended lifespans in animal models. The mechanism by which methionine restriction inhibits tumor growth while sparing normal cells is not fully understood.
View Article and Find Full Text PDFJ Am Stat Assoc
June 2024
Department of Statistics, University of Wisconsin, Madison, WI, USA, 53706.
Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with the epigenome at the single cell level. While methods to analyze data from single cell high throughput chromatin conformation capture (scHi-C) experiments are maturing, methods that can jointly analyze multiple single cell modalities with scHi-C data are lacking. Here, we introduce Muscle, a semi-nonnegative joint decomposition of Multiple single cell tensors, to jointly analyze 3D conformation and DNA methylation data at the single cell level.
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