An intelligent rapid odour recognition model in discrimination of Helicobacter pylori and other gastroesophageal isolates in vitro

Pavlou, Alexandros; Magan, Naresh; Sharp, D.; Brown, John; Barr, Hugh; Turner, Anthony P. F.

doi:10.1016/s0956-5663(99)00035-4

Cited by 89 publications

(55 citation statements)

References 33 publications

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“…Overall, in the context of previous studies documenting alterations in exhaled gases of patients with lung cancer (9)(10)(11)(12)(13)(14)(15), this study demonstrates the feasibility of clinical monitoring of VOCs in exhaled breath using a multisensor electronic nose as a relatively convenient and noninvasive test in patients with suspected lung cancer.…”

Section: Discussionsupporting

confidence: 65%

“…There may be potential utility for electronic nose technology in medical applications, including identification of bacterial pathogens (6,7,9,10) and pneumonia (8), and monitoring of glucose control in patients with diabetes (11). In this context, many VOCs, in particular alkanes and benzene derivatives, measured by mass spectrometry of the exhaled breath have been used to predict the presence of lung cancer in patients (12,13).…”

mentioning

confidence: 99%

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Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

Machado

Laskowski²,

Deffenderfer³

et al. 2005

Am J Respir Crit Care Med

537

429

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Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. Main Results: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. Conclusion: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.

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Section: Discussionsupporting

confidence: 65%

mentioning

confidence: 99%

Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

Machado

Laskowski²,

Deffenderfer³

et al. 2005

Am J Respir Crit Care Med

537

429

View full text Add to dashboard Cite

show abstract

“…These and several other studies [46][47][48][49][50][51] prove that an electronic nose reacts on volatile products of microbial metabolism, and that it can detect the presence of microorganisms in different kinds of samples.…”

Section: Electronic Nosesupporting

confidence: 52%

05/01826 Microbial volatile organic compounds as indicators of fungi. Can an electronic nose detect fungi in indoor environments?

2005

Fuel and Energy Abstracts

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Abstract:The paper presents a review of several studies on the detection of microbial volatile organic compounds (MVOCs) considered as indicators of fungal contamination. As fungi produce specific profiles, or fingerprints of volatile compounds, the electronic nose technology is a very promising opportunity for rapid and non costly detection of fungi in buildings. E-noses are able to distinguish between mouldy and non-mouldy samples, and also to recognise certain species of fungi. However, two limiting factors may appear decisive for employment of electronic noses in indoor fungi detection: low concentrations of MVOCs and presence of interfering substances in indoor environments.

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“…In human medicine, 'artificial' or 'electronic' nose (e-nose) technology has been employed in several areas of medical diagnosis, including rapid detection of tuberculosis [1], Helicobacter pylori [2], bacterial sinusitis [3] and urinary tract infections [4,5]. In veterinary medicine, the usefulness of e-nose technology was principally demonstrated for the first time in 2005 by discriminating serum samples obtained from badgers and cattle infected with Mycobacterium bovis from those obtained in non-infected controls [6].…”

Section: Introductionmentioning

confidence: 99%