AIMC Topic: Proton Magnetic Resonance Spectroscopy
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From NMR to AI: Do We Need H NMR Experimental Spectra to Obtain High-Quality logD Prediction Models?
Journal of chemical information and modeling
Mar 5, 2025
This study presents a novel approach to H NMR-based machine learning (ML) models for predicting logD using computer-generated H NMR spectra. Building on our previous work, which integrated experimental H NMR data, this study addresses key limitations...
Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.
BMC gastroenterology
Feb 6, 2025
BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.
Detecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.
Computers in biology and medicine
Jan 27, 2025
BACKGROUND: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations in glioma is critical for prognosis and treatment planning. This study aims to develop deep lear...
NMRformer: A Transformer-Based Deep Learning Framework for Peak Assignment in 1D H NMR Spectroscopy.
Analytical chemistry
Jan 2, 2025
Metabolite identification from 1D H NMR spectra is a major challenge in NMR-based metabolomics. This study introduces NMRformer, a Transformer-based deep learning framework for accurate peak assignment and metabolite identification in 1D H NMR spectr...
WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.
Magnetic resonance in medicine
Dec 31, 2024
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...
Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.
Molecules (Basel, Switzerland)
Dec 13, 2024
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...
Recurrent neural network-aided processing of incomplete free induction decays in H-MRS of the brain.
Journal of magnetic resonance (San Diego, Calif. : 1997)
Sep 12, 2024
In the case of limited sampling windows or truncation of free induction decays (FIDs) for artifact removal in proton magnetic resonance spectroscopy (H-MRS) and spectroscopic imaging (H-MRSI), metabolite quantification needs to be performed on incomp...
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...
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 ...
A review of machine learning applications for the proton MR spectroscopy workflow.
Magnetic resonance in medicine
Jul 4, 2023
This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured over...
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