AIMC Topic: Metabolomics
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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...
Deep learning-based metabolomics data study of prostate cancer.
BMC bioinformatics
Dec 26, 2024
As a heterogeneous disease, prostate cancer (PCa) exhibits diverse clinical and biological features, which pose significant challenges for early diagnosis and treatment. Metabolomics offers promising new approaches for early diagnosis, treatment, and...
From multi-omics to predictive biomarker: AI in tumor microenvironment.
Frontiers in immunology
Dec 23, 2024
In recent years, tumors have emerged as a major global health threat. An increasing number of studies indicate that the production, development, metastasis, and elimination of tumor cells are closely related to the tumor microenvironment (TME). Advan...
Evaluation of a machine learning-based metabolic marker for coronary artery disease in the UK Biobank.
Atherosclerosis
Dec 18, 2024
BACKGROUND AND AIMS: An in silico quantitative score of coronary artery disease (ISCAD), built using machine learning and clinical data from electronic health records, has been shown to result in gradations of risk of subclinical atherosclerosis, cor...
Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning algorithms.
Science advances
Dec 18, 2024
Biological aging clocks produce age estimates that can track with age-related health outcomes. This study aimed to benchmark machine learning algorithms, including regularized regression, kernel-based methods, and ensembles, for developing metabolomi...
Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC-MS urinary metabolomics for diseases screening.
International journal of medical informatics
Dec 16, 2024
BACKGROUND: Gas chromatography-mass spectrometry (GC-MS) has been shown to be a potentially efficient metabolic profiling platform in urine analysis. However, the widespread use of GC-MS for inborn errors of metabolism (IEM) screening is constrained ...
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...
Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.
Frontiers in immunology
Dec 13, 2024
BACKGROUND: Cancer remains a leading cause of mortality worldwide. A non-invasive screening solution was required for early diagnosis of cancer. Multi-cancer early detection (MCED) tests have been considered to address the challenge by simultaneously...
Uncertainty Quantification and Flagging of Unreliable Predictions in Predicting Mass Spectrometry-Related Properties of Small Molecules Using Machine Learning.
International journal of molecular sciences
Dec 5, 2024
Mass spectral identification (in particular, in metabolomics) can be refined by comparing the observed and predicted properties of molecules, such as chromatographic retention. Significant advancements have been made in predicting these values using ...
Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status.
International journal of molecular sciences
Dec 4, 2024
Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently. Breast cancer subtyping based on estrogen receptor (ER) status is crucial for determining prognosis...
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