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dc.contributor.authorVidal, Plácido
dc.contributor.authorMoura, Joaquim de
dc.contributor.authorRamos, Lucía
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2020-10-27T17:52:44Z
dc.date.available2020-10-27T17:52:44Z
dc.date.issued2020-08-26
dc.identifier.citationVidal, P.L.; Moura, J.d.; Ramos, L.; Novo, J.; Ortega, M. Study on Relevant Features in COVID-19 PCR Tests. Proceedings 2020, 54, 45. https://doi.org/10.3390/proceedings2020054045es_ES
dc.identifier.issn2504-3900
dc.identifier.urihttp://hdl.handle.net/2183/26557
dc.description.abstract[Abstract] In the year 2020, the world suffered the effects of a global pandemic. COVID-19 is a disease that mainly affects the respiratory system of patients, even causing a disproportionate response of the immune system and further spreading the damage to other vital organs. The main means by which health care services detected this viral disease was through the use of Polymerase Chain Reactions (PCRs). These PCRs allow the detection of known chains of the genetic code of the virus in samples of sputum. In this work, we study PCR signal features that allow to automatize the analysis of hundreds of PCRs. The findings obtained from the study have shown these features to be capable of obtaining successful results in the detection of COVID-19 in PCR samples, with only a small fraction of the information extracted by the clinicians for that purpose.es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipInstituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia, Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project, Ayudas para la formación de profesorado universitario (FPU), grant ref. FPU18/02271; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, receives financial support from Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaría Xeral de Universidades (20%).
dc.language.isoenges_ES
dc.publisherMDPI AGes_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/DTS18%2F00136/ES/Plataforma online para prevención y detección precoz de enfermedad vascular mediante análisis automatizado de información e imagen clínica
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095894-B-I00/ES/DESARROLLO DE TECNOLOGIAS INTELIGENTES PARA DIAGNOSTICO DE LA DMAE BASADAS EN EL ANALISIS AUTOMATICO DE NUEVAS MODALIDADES HETEROGENEAS DE ADQUISICION DE IMAGEN OFTALMOLOGICA
dc.relationinfo:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU18%2F02271/ES/
dc.relation.urihttps://doi.org/10.3390/proceedings2020054045es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)es_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectPolymerase chain reactiones_ES
dc.subjectCOVID-19es_ES
dc.subjectFeature analysises_ES
dc.titleStudy on Relevant Features in COVID-19 PCR Testses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleProceedingses_ES
UDC.volume54es_ES
UDC.issue1es_ES
UDC.startPage45es_ES
dc.identifier.doi10.3390/proceedings2020054045
UDC.conferenceTitle3rd XoveTIC Conference; A Coruña, Spain; 8–9 October 2020es_ES


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