Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractMalodour classification with low-cost flexible electronics    Next AbstractLong-range atmospheric transport of three toxaphene congeners across Europe. Modeling by chained single-box FATEMOD program »

J Breath Res


Title:Breath VOC analysis and machine learning approaches for disease screening: a review
Author(s):P H; Rangarajan M; Pandya HJ;
Address:"Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India. Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India"
Journal Title:J Breath Res
Year:2023
Volume:20230203
Issue:2
Page Number: -
DOI: 10.1088/1752-7163/acb283
ISSN/ISBN:1752-7163 (Electronic) 1752-7155 (Linking)
Abstract:"Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition"
Keywords:Humans *Breath Tests/methods *Volatile Organic Compounds/analysis Biomarkers/analysis Exhalation Machine Learning electronic nose (E-nose) exhaled breath head and neck cancer liver diseases sensor array volatile organic compounds;
Notes:"MedlineP, Haripriya Rangarajan, Madhavan Pandya, Hardik J eng Review England 2023/01/13 J Breath Res. 2023 Feb 3; 17(2). doi: 10.1088/1752-7163/acb283"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 17-11-2024