AIMC Topic: Gas Chromatography-Mass Spectrometry
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Accessible halitosis diagnosis: validating the accuracy of novel AI-based compact VSC measuring instrument.
Journal of breath research
Jan 31, 2025
Halitosis presents a significant global health concern, necessitating the development of precise and efficient testing methodologies owing to the high prevalence and the associated social and psychological effects. The measurement of volatile sulfur ...
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 ...
Effective detection of indoor fungal contamination through the identification of volatile organic compounds using mass spectrometry and machine learning.
Environmental pollution (Barking, Essex : 1987)
Oct 28, 2024
Indoor fungal contamination poses significant challenges to human health and indoor air quality. This study addresses an effective approach using mass spectrometry and machine learning to identify microbial volatile organic compounds (MVOCs) originat...
Development of analytical "aroma wheels" for Oolong tea infusions (Shuixian and Rougui) and prediction of dynamic aroma release and colour changes during "Chinese tea ceremony" with machine learning.
Food chemistry
Oct 4, 2024
The flavour of tea as a worldwide popular beverage has been studied extensively. This study aimed to apply established flavour analysis techniques (GC-MS, GC-O-MS and APCI-MS/MS) in innovative ways to characterise the flavour profile of oolong tea in...
A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.
Clinica chimica acta; international journal of clinical chemistry
Sep 24, 2024
BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality rates among newborns. Recognizing the profound impact of neonatal sepsis on long-term health outcomes emphasizes the critical need for timely detectio...
Discrimination of coal geographical origins through HS-GC-IMS assisted with machine learning algorithms in larceny case.
Journal of chromatography. A
Aug 30, 2024
The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection ...
RSM and ANN-Based Optimized Ultrasound-Assisted Extraction of Functional Components from Olive Fruit (cv Arbequina): Assessment of Antioxidant Attributes and GC-MS Metabolites Profiling.
Chemistry & biodiversity
Aug 30, 2024
The current study devises an optimized ethanolic extraction for efficient recovery of high-value components from Pakistani olives (cv. Arbequina) using response surface methodology (RSM) and artificial neural networking (ANN). Four factors such as ti...
Novel Strategy for Human Deep Vein Thrombosis Diagnosis Based on Metabolomics and Stacking Machine Learning.
Analytical chemistry
Aug 28, 2024
Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learni...
Chemometrics methods, sensory evaluation and intelligent sensory technologies combined with GAN-based integrated deep-learning framework to discriminate salted goose breeds.
Food chemistry
Aug 22, 2024
The authenticity of salted goose products is concerning for consumers. This study describes an integrated deep-learning framework based on a generative adversarial network and combines it with data from headspace solid phase microextraction/gas chrom...
An initial exploration of machine learning for establishing associations between genetic markers and THC levels in Cannabis sativa samples.
Forensic science international. Genetics
Aug 9, 2024
Cannabis sativa, a globally commercialized plant used for medicinal, food, fiber production, and recreation, necessitates effective identification to distinguish legal and illegal varieties in forensic contexts. This research utilizes multivariate st...
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