AIMS: To evaluate the electronic nose (EN) as method for the identification of ten clinically important micro-organisms. METHODS AND RESULTS: A commercial EN system with a series of ten metal oxide sensors was used to characterize the headspace of the cultured organisms. The measurement procedure was optimized to obtain reproducible results. Artificial neural networks (ANNs) and a k-nearest neighbour (k-NN) algorithm in combination with a feature selection technique were used as pattern recognition tools. Hundred percent correct identification can be achieved by EN technology, provided that sufficient attention is paid to data handling. CONCLUSIONS: Even for a set containing a number of closely related species in addition to four unrelated organisms, an EN is capable of 100% correct identification. SIGNIFICANCE AND IMPACT OF THE STUDY: The time between isolation and identification of the sample can be dramatically reduced to 17 h.
AIMS: To evaluate the electronic nose (EN) as method for the identification of ten clinically important micro-organisms. METHODS AND RESULTS: A commercial EN system with a series of ten metal oxide sensors was used to characterize the headspace of the cultured organisms. The measurement procedure was optimized to obtain reproducible results. Artificial neural networks (ANNs) and a k-nearest neighbour (k-NN) algorithm in combination with a feature selection technique were used as pattern recognition tools. Hundred percent correct identification can be achieved by EN technology, provided that sufficient attention is paid to data handling. CONCLUSIONS: Even for a set containing a number of closely related species in addition to four unrelated organisms, an EN is capable of 100% correct identification. SIGNIFICANCE AND IMPACT OF THE STUDY: The time between isolation and identification of the sample can be dramatically reduced to 17 h.
Authors: Theodore R Mellors; Christiaan A Rees; Flavio A Franchina; Alison Burklund; Chaya Patel; Lucy J Hathaway; Jane E Hill Journal: J Chromatogr B Analyt Technol Biomed Life Sci Date: 2018-08-29 Impact factor: 3.205
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Authors: K de Heer; M G M Kok; N Fens; E J M Weersink; A H Zwinderman; M P C van der Schee; C E Visser; M H J van Oers; P J Sterk Journal: J Clin Microbiol Date: 2015-12-16 Impact factor: 5.948
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Authors: Claire L Lonsdale; Brian Taba; Nuria Queralto; Roman A Lukaszewski; Raymond A Martino; Paul A Rhodes; Sung H Lim Journal: PLoS One Date: 2013-05-09 Impact factor: 3.240