AIMC Topic: Magnetic Resonance Spectroscopy
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Self-organizing maps for exploration and classification of nuclear magnetic resonance spectra for untargeted metabolomics of breast cancer.
Journal of pharmaceutical and biomedical analysis
Jul 21, 2024
Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within met...
Resolution Enhancement of Metabolomic J-Res NMR Spectra Using Deep Learning.
Analytical chemistry
Jul 11, 2024
J-Resolved (J-Res) nuclear magnetic resonance (NMR) spectroscopy is pivotal in NMR-based metabolomics, but practitioners face a choice between time-consuming high-resolution (HR) experiments or shorter low-resolution (LR) experiments which exhibit si...
Enhancing Chemical Reaction Monitoring with a Deep Learning Model for NMR Spectra Image Matching to Target Compounds.
Journal of chemical information and modeling
Jul 9, 2024
In the synthetic laboratory, researchers typically rely on nuclear magnetic resonance (NMR) spectra to elucidate structures of synthesized products and confirm whether they match the desired target compounds. As chemical synthesis technology evolves ...
Fusing H NMR and Raman experimental data for the improvement of wine recognition models.
Food chemistry
Jun 26, 2024
The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector ...
The intelligent imaging revolution: artificial intelligence in MRI and MRS acquisition and reconstruction.
Magma (New York, N.Y.)
Jun 20, 2024
Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal.
IEEE transactions on bio-medical engineering
May 20, 2024
OBJECTIVE: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of...
Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks.
Magnetic resonance imaging
May 12, 2024
PURPOSE: To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edite...
Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.
Magma (New York, N.Y.)
Apr 13, 2024
PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete sc...
From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.
Journal of chemical information and modeling
Mar 26, 2024
A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was e...
Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study.
Scientific reports
Mar 7, 2024
In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the microstructure of myocardial tissue in living hearts, providing insights into cardiac function and enabling the development o...
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