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Sci Rep

Title:		Machine learning for the meta-analyses of microbial pathogens' volatile signatures
Author(s):		Palma S; Traguedo AP; Porteira AR; Frias MJ; Gamboa H; Roque ACA;
Address:		"UCIBIO, REQUIMTE, Departamento de Quimica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. LIBPhys-UNL, Departamento de Fisica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. UCIBIO, REQUIMTE, Departamento de Quimica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal. cecilia.roque@fct.unl.pt"
Journal Title:		Sci Rep
Year:		2018
Volume:		20180220
Issue:		1
Page Number:		3360 -
DOI:		10.1038/s41598-018-21544-1
ISSN/ISBN:		2045-2322 (Electronic) 2045-2322 (Linking)
Abstract:		"Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices"
Keywords:		"Biological Factors/*analysis Chemistry Techniques, Analytical/*methods Communicable Diseases/*diagnosis/*microbiology Humans *Machine Learning Metabolomics/*methods Volatile Organic Compounds/*analysis;"
Notes:		"MedlinePalma, Susana I C J Traguedo, Ana P Porteira, Ana R Frias, Maria J Gamboa, Hugo Roque, Ana C A eng 639123/ERC_/European Research Council/International Meta-Analysis Research Support, Non-U.S. Gov't England 2018/02/22 Sci Rep. 2018 Feb 20; 8(1):3360. doi: 10.1038/s41598-018-21544-1"