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Study on Relevant Features in COVID-19 PCR Tests
dc.contributor.author | Vidal, Plácido | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Ramos, Lucía | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2020-10-27T17:52:44Z | |
dc.date.available | 2020-10-27T17:52:44Z | |
dc.date.issued | 2020-08-26 | |
dc.identifier.citation | Vidal, 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/proceedings2020054045 | es_ES |
dc.identifier.issn | 2504-3900 | |
dc.identifier.uri | http://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.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Instituto 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.iso | eng | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation | info: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.relation | info: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.relation | info:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU18%2F02271/ES/ | |
dc.relation.uri | https://doi.org/10.3390/proceedings2020054045 | es_ES |
dc.rights | Atribución 4.0 Internacional (CC BY 4.0) | es_ES |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Polymerase chain reaction | es_ES |
dc.subject | COVID-19 | es_ES |
dc.subject | Feature analysis | es_ES |
dc.title | Study on Relevant Features in COVID-19 PCR Tests | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Proceedings | es_ES |
UDC.volume | 54 | es_ES |
UDC.issue | 1 | es_ES |
UDC.startPage | 45 | es_ES |
dc.identifier.doi | 10.3390/proceedings2020054045 | |
UDC.conferenceTitle | 3rd XoveTIC Conference; A Coruña, Spain; 8–9 October 2020 | es_ES |