AIMC Topic: Electronic Nose

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Discrimination of Respiratory Tract Infections by a Reduced Graphene Oxide Array Modified with Metal-Organic Frameworks and Metal Phthalocyanines.

ACS nano May 16, 2025
As a prevalent clinical condition, it is critical to distinguish between bacterial and viral respiratory tract infections given their pivotal role in guiding appropriate pharmaceutical interventions and preventing antibiotic misuse. Exhaled breath (E...
Humans Male Metal-Organic Frameworks Isoindoles Graphite Respiratory Tract Infections Indoles Breath Tests Electronic Nose
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Gas Sensor Drift Compensation Using Semi-Supervised Ensemble Classifiers with Multi-Level Features and Center Loss.

ACS sensors Apr 8, 2025
The drift compensation of gas sensors is a significant and challenging issue in the field of electronic noses (E-nose). Compensating sensor drift has a great benefit in improving the performance of E-nose systems. However, conventional methods often ...
Gases Electronic Nose Neural Networks, Computer Algorithms
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Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review.

Food research international (Ottawa, Ont.) Mar 17, 2025
The growing concern over food safety, driven by threats such as food contaminations and adulterations has prompted the adoption of advanced technologies like electronic nose (e-nose) and hyperspectral imaging (HSI), which are increasingly enhanced by...
Hyperspectral Imaging Machine Learning Food Safety Electronic Nose Humans Deep Learning Neural Networks, Computer Food Contamination
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Leaf-Face Classifier Based on an Integrated Electrochemical Tongue and Machine Learning.

ACS sensors Feb 4, 2025
Botanical sourcing seriously impacts the safety and potency of herbal medicines, restricting the development of the traditional Chinese medicinal industry. Rapid and convenient identification of plant resources is important to address this problem. H...
Electrochemical Techniques Dendrobium Electronic Nose Machine Learning Plant Leaves
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Machine learning-based classification and prediction of typical Chinese green tea taste profiles.

Food research international (Ottawa, Ont.) Jan 27, 2025
The taste of Chinese green tea is highly diverse. In this study, a combination of unsupervised and supervised learning methods was utilized to develop a model for classifying and predicting typical Chinese green tea taste. Three clustering methods we...
Tea Taste Catechin Cluster Analysis Metabolomics Electronic Nose Machine Learning Adult Spectroscopy, Near-Infrared China Male Humans
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Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food.

Toxins Dec 23, 2024
Zearalenone (ZEN) has been detected in both pet food ingredients and final products, causing acute toxicity and chronic health problems in pets. Therefore, the early detection of mycotoxin contamination in pet food is crucial for ensuring the safety ...
Pets Electronic Nose Tandem Mass Spectrometry Volatile Organic Compounds Machine Learning Zearalenone Animals Animal Feed Food Contamination
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Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm-optimized backpropagation neural network.

PloS one Dec 3, 2024
Ammonia is widely acknowledged to be a stressor and one of the most detrimental gases in animal enclosures. In livestock- and poultry-breeding facilities, a precise, rapid, and affordable method for detecting ammonia concentrations is essential. We d...
Dogs Ammonia Electronic Nose Bionics Algorithms Animals Humans Neural Networks, Computer Ethanol
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Feasibility of classification of drainage and river water quality using machine learning methods based on multidimensional data from a gas sensor array.

Annals of agricultural and environmental medicine : AAEM Dec 2, 2024
OBJECTIVE: The aim of the study is to verify whether the electronic nose system - an array of 17 gas sensors with a signal analysis system - is a useful tool for the classification and preliminary assessment of the quality of drainage water.
Machine Learning Poland Neural Networks, Computer Electronic Nose Water Quality Rivers Environmental Monitoring Gases Feasibility Studies
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Noninvasive Total Cholesterol Level Measurement Using an E-Nose System and Machine Learning on Exhaled Breath Samples.

ACS sensors Nov 22, 2024
In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a ...
Electronic Nose Female Young Adult Adult Humans Cholesterol Machine Learning Algorithms Breath Tests Male Exhalation Middle Aged
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TC-Sniffer: A Transformer-CNN Bibranch Framework Leveraging Auxiliary VOCs for Few-Shot UBC Diagnosis via Electronic Noses.

ACS sensors Nov 13, 2024
Utilizing electronic noses (e-noses) with pattern recognition algorithms offers a promising noninvasive method for the early detection of urinary bladder cancer (UBC). However, limited clinical samples often hinder existing artificial intelligence (A...
Volatile Organic Compounds Electronic Nose Humans Algorithms Neural Networks, Computer Urinary Bladder Neoplasms
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