Paper Info
Title
Intelligent gas-sensing systems for bacterial clinical isolates in vitro classification
Abstract
Sensorial analysis based on the utilisation of human senses, is one of the most important and straightforward investigation methods in food and chemical analysis. Recently, the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence. It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage. A newly developed "artificial nose" based on chemoresistive sensors has been employed to identify in vitro 13 bacterial clinical isolates, collected from patients diagnosed with urinary tract infections, gastrointestinal and respiratory infections in a UK Public Health Laboratory environment. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on Neural Networks has been applied in the identification and characterisation of microbial pathogens. The study adopts a soft fusion concept of the outputs of multiple classifiers dedicated to specific feature parameters. The experimental results confirm the validity of the presented method.
Year
Venue
Keywords
2005
Neural Parallel & Scientific Comp.
artificial intelligence,chemical analysis,intelligent gas-sensing system,sensorial analysis,artificial nose,vitro classification,clinical diagnosis,odour generation mechanism,classifier system,recovery system,specific odours characteristic,specific feature parameter,feature selection,neural networks
Field
DocType
Volume
Disease,Sensing system,Feature selection,Computer science,Clinical diagnosis,Artificial intelligence,Artificial neural network,Classifier (linguistics),Machine learning
Journal
13
Issue
Citations 
PageRank 
2
0
0.34
References 
Authors
2
1
Name
Order
Citations
PageRank
Vassilis S. Kodogiannis127235.17