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Distinction of different colony types by a smart-data-driven tool

dc.contributor.authorRodrigues, Pedro Miguel
dc.contributor.authorRibeiro, Pedro
dc.contributor.authorTavaria, Freni Kekhasharú
dc.date.accessioned2023-01-05T11:11:08Z
dc.date.available2023-01-05T11:11:08Z
dc.date.issued2023
dc.description.abstractBackground: Colony morphology (size, color, edge, elevation, and texture), as observed on culture media, can be used to visually discriminate different microorganisms. Methods: This work introduces a hybrid method that combines standard pre-trained CNN keras models and classical machine-learning models for supporting colonies discrimination, developed in Petri-plates. In order to test and validate the system, images of three bacterial species (Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) cultured in Petri plates were used. Results: The system demonstrated the following Accuracy discrimination rates between pairs of study groups: 92% for Pseudomonas aeruginosa vs. Staphylococcus aureus, 91% for Escherichia coli vs. Staphylococcus aureus and 84% Escherichia coli vs. Pseudomonas aeruginosa. Conclusions: These results show that combining deep-learning models with classical machine-learning models can help to discriminate bacteria colonies with good accuracy ratios.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/bioengineering10010026pt_PT
dc.identifier.eid85146835362
dc.identifier.issn2306-5354
dc.identifier.pmid36671597
dc.identifier.urihttp://hdl.handle.net/10400.14/39741
dc.identifier.wos000916494300001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPetri-platespt_PT
dc.subjectColoniespt_PT
dc.subjectMachine-learning modelspt_PT
dc.subjectDiscriminationpt_PT
dc.titleDistinction of different colony types by a smart-data-driven toolpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue1pt_PT
oaire.citation.titleBioengineeringpt_PT
oaire.citation.volume10pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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