Literature DB >> 10834396

Sniffing out the truth: clinical diagnosis using the electronic nose.

A K Pavlou1, A P Turner.   

Abstract

Recently the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence (AI). It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage. Later chromatographic techniques identified an enormous number of volatiles in human clinical specimens that might serve as potential disease markers. "Artificial nose" technology has been employed in several areas of medical diagnosis, including rapid detection of tuberculosis (TB), Helicobacter pylori (HP) and urinary tract infections (UTI). Preliminary results have demonstrated the possibility of identifying and characterising microbial pathogens in clinical specimens. A hybrid intelligent model of four interdependent "tools", odour generation "kits", rapid volatile delivery and recovery systems, consistent low drift sensor performance and a hybrid intelligent system of parallel neural networks (NN) and expert systems, have been applied in gastric, pulmonary and urine diagnosis. Initial clinical tests have shown that it may be possible in the near future to use electronic nose technology not only for the rapid detection of diseases such as peptic ulceration, UTI, and TB but also for the continuous dynamic monitoring of disease stages. Major advances in information and gas sensor technology could enhance the diagnostic power of future bio-electronic noses and facilitate global surveillance models of disease control and management.

Entities:  

Mesh:

Substances:

Year:  2000        PMID: 10834396     DOI: 10.1515/CCLM.2000.016

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  15 in total

Review 1.  Advances in electronic-nose technologies developed for biomedical applications.

Authors:  Alphus D Wilson; Manuela Baietto
Journal:  Sensors (Basel)       Date:  2011-01-19       Impact factor: 3.576

2.  Scent of a patient: an underestimated role in clinical practice?

Authors:  Martina Kelly
Journal:  Br J Gen Pract       Date:  2012-07       Impact factor: 5.386

3.  Prospects for clinical application of electronic-nose technology to early detection of Mycobacterium tuberculosis in culture and sputum.

Authors:  Reinhard Fend; Arend H J Kolk; Conrad Bessant; Patricia Buijtels; Paul R Klatser; Anthony C Woodman
Journal:  J Clin Microbiol       Date:  2006-06       Impact factor: 5.948

4.  Use of an electronic nose to diagnose Mycobacterium bovis infection in badgers and cattle.

Authors:  R Fend; R Geddes; S Lesellier; H-M Vordermeier; L A L Corner; E Gormley; E Costello; R G Hewinson; D J Marlin; A C Woodman; M A Chambers
Journal:  J Clin Microbiol       Date:  2005-04       Impact factor: 5.948

Review 5.  Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities.

Authors:  Linda M Parsons; Akos Somoskövi; Cristina Gutierrez; Evan Lee; C N Paramasivan; Alash'le Abimiku; Steven Spector; Giorgio Roscigno; John Nkengasong
Journal:  Clin Microbiol Rev       Date:  2011-04       Impact factor: 26.132

6.  Production of bioactive volatiles by different Burkholderia ambifaria strains.

Authors:  Ulrike Groenhagen; Rita Baumgartner; Aurélien Bailly; Amber Gardiner; Leo Eberl; Stefan Schulz; Laure Weisskopf
Journal:  J Chem Ecol       Date:  2013-07-07       Impact factor: 2.626

Review 7.  Clinical application of volatile organic compound analysis for detecting infectious diseases.

Authors:  Shneh Sethi; Ranjan Nanda; Trinad Chakraborty
Journal:  Clin Microbiol Rev       Date:  2013-07       Impact factor: 26.132

Review 8.  Human skin volatiles: a review.

Authors:  Laurent Dormont; Jean-Marie Bessière; Anna Cohuet
Journal:  J Chem Ecol       Date:  2013-04-25       Impact factor: 2.626

Review 9.  Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review.

Authors:  Kim D G van de Kant; Linda J T M van der Sande; Quirijn Jöbsis; Onno C P van Schayck; Edward Dompeling
Journal:  Respir Res       Date:  2012-12-21

10.  Predicting the receptive range of olfactory receptors.

Authors:  Rafi Haddad; Liran Carmel; Noam Sobel; David Harel
Journal:  PLoS Comput Biol       Date:  2008-02       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.