AIMC Topic: Electronic Nose

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Electronic-Nose Technology for Lung Cancer Detection: A Non-Invasive Diagnostic Revolution.

Lung
BACKGROUND: Lung cancer (LC) remains a leading cause of cancer-related mortality worldwide, primarily due to late-stage diagnosis and the absence of effective early detection methods.

Impact of ginger juice processing on volatile compounds and sensory characteristics of Eucommiae Cortex: A GC×GC-TOF-MS, E-nose, and machine learning analysis.

Journal of pharmaceutical and biomedical analysis
Ginger-processed Eucommiae Cortex (G-EC) is a traditional herbal preparation with a long history of clinical application. However, the lack of quantitative standards, undefined chemical transformation pathways, and unidentified quality markers (Q-mar...

Electronic nose, HS-GC-IMS, HS-SPME-GC-MS, and deep learning model were used to analyze and predict the changes and contents of VOCs in in-shell walnut kernels under different roasting conditions.

Food chemistry
Roasting imparts walnuts with an increased amount of hedonic aromas. Consequently, this study comprehensively analyzed aroma characteristics of in-shell walnut kernels during roasting at different conditions using quantitative descriptive analysis, E...

Flavor characterization of aged Citri Reticulatae Pericarpium from core regions: An integrative approach utilizing GC-IMS, GC-MS, E-nose, E-tongue, and chemometrics.

Food chemistry
This study utilized GC-MS, GC-IMS, E-nose, and E-tongue to analyze the flavor characteristics of Guangchenpi (GCP) from five core producing areas aged 5 to 40 years. Key findings include: W1W, W2S, and W5S sensors in the e-nose and bitter, umami, swe...

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

ACS nano
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...

Gas Sensor Drift Compensation Using Semi-Supervised Ensemble Classifiers with Multi-Level Features and Center Loss.

ACS sensors
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 ...

Rapid evaluation of Curcuma origin and quality based on E-eye, flash GC e-nose, and FT-NIR combined with machine learning technologies.

Food chemistry
Curcuma, a key ingredient in curry and a popular health supplement, has been subject to adulteration and fraudulent origin labeling. In this study, E-eye, Flash GC e-nose, and FT-NIR, combined with machine learning and multivariate algorithms, were e...

Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review.

Food research international (Ottawa, Ont.)
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...

Leaf-Face Classifier Based on an Integrated Electrochemical Tongue and Machine Learning.

ACS sensors
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...

Machine learning-based classification and prediction of typical Chinese green tea taste profiles.

Food research international (Ottawa, Ont.)
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...