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dc.contributor.authorRacedo, Jorge
dc.date.accessioned2021-06-29T21:18:04Z
dc.date.available2021-06-29T21:18:04Z
dc.date.issued2021-06-28
dc.identifier.urihttp://hdl.handle.net/1992/50201
dc.description.abstractMost hospitals and government offices in Colombia have no centralized systems to efficiently collect data for evidence generation for academic purposes and policymaking. In addition, physicians in small-to-middle-size cities do not participate in conducting clinical research due to significant gaps in resources and personnel skilled in data science. It results in a lack of information about the prevalence and impact of diseases, limiting municipalities' power to decide when developing prevention, screeningdiagnosis, and treatment programs. microscopIA, through the current approach, has grown a platform to allow physicians to collect data matching a research project while collecting massive data for AI training and policymakinges_CO
dc.formatapplication/pdfes_CO
dc.format.extent22 hojases_CO
dc.language.isoenges_CO
dc.sourceinstname:Universidad de los Andeses_CO
dc.sourcereponame:Repositorio Institucional Sénecaes_CO
dc.titleAI training for automated data extraction from clinical recordses_CO
dc.typeReportees_CO
dc.rights.accessRightsopenAccesses_CO
dc.subject.keywordGestión de datoses_CO
dc.subject.keywordInteligencia artificiales_CO
dc.subject.keywordHospitaleses_CO
dc.type.versionpublishedVersiones_CO


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