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dc.contributor.authorLopez-Cortes X.A.
dc.contributor.authorAvila-Salas F.
dc.contributor.authorOrellana C.
dc.contributor.authorSantos L.S.
dc.date.accessioned2020-09-02T22:21:47Z
dc.date.available2020-09-02T22:21:47Z
dc.date.issued2019
dc.identifier10.1109/ICA-ACCA.2018.8609735
dc.identifier.urihttps://hdl.handle.net/20.500.12728/5101
dc.descriptionPiscirickettsia salmonis is a highly transmissible pathogens that cause high mortality in farmed salmonids. In this way, new techniques based on mass spectrometry (MS) and machine learning were applied and combined in an automatized platform in order to classify and predict this pathogen, in a faster and effective way. MALDI-MS was used to analyze serum samples from salmonid fishes (healthy and diseased) coupled to machine learning analysis in order to obtain a specific and sensitive pattern (m/z) for every pathogen with high reproducibility. The results probed that combining these two techniques are a powerful tool in the correct detection of this pathogen, in an early state of the infection process. Accuracy was >80%, which affords the good performance of our platform as a potential tool for the early disease control in the salmon farming industry. © 2018 IEEE.
dc.language.isoes
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.sourceMunoz C.Lefranc G.Fernandez-Fernandez M.Rubio E.Duran-Faundez C.
dc.subjectData mining
dc.subjectDatabases
dc.subjectDisease control
dc.subjectFingerprint recognition
dc.subjectMachine learning
dc.subjectAutomation
dc.subjectDatabase systems
dc.subjectDisease control
dc.subjectIndustry 4.0
dc.subjectLearning systems
dc.subjectMachine learning
dc.subjectMass spectrometry
dc.subjectPathogens
dc.subjectPattern recognition
dc.subjectProcess control
dc.subjectFingerprint Recognition
dc.subjectHigh reproducibility
dc.subjectInfection process
dc.subjectMALDI-mass spectrometry
dc.subjectPotential tool
dc.subjectSalmon farming industry
dc.subjectSalmonid fish
dc.subjectSerum samples
dc.subjectData mining
dc.titleStrategy based on data mining and MALDI-mass spectrometry for control disease of SRS in salmo salar
dc.typeConference Paper


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