AI training for automated data extraction from clinical records

Most 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...

Full description

Autores:
Racedo Galván, Jorge Mario
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2022
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/58181
Acceso en línea:
http://hdl.handle.net/1992/58181
Palabra clave:
Artificial intelligence
Clinical research
Federated learning
Aprendizaje automático (Inteligencia artificial)
Ingeniería
Rights
openAccess
License
Attribution-NoDerivatives 4.0 Internacional
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dc.title.none.fl_str_mv AI training for automated data extraction from clinical records
dc.title.alternative.none.fl_str_mv microscopIA
title AI training for automated data extraction from clinical records
spellingShingle AI training for automated data extraction from clinical records
Artificial intelligence
Clinical research
Federated learning
Aprendizaje automático (Inteligencia artificial)
Ingeniería
title_short AI training for automated data extraction from clinical records
title_full AI training for automated data extraction from clinical records
title_fullStr AI training for automated data extraction from clinical records
title_full_unstemmed AI training for automated data extraction from clinical records
title_sort AI training for automated data extraction from clinical records
dc.creator.fl_str_mv Racedo Galván, Jorge Mario
dc.contributor.advisor.none.fl_str_mv Bigio Roitman, David
dc.contributor.author.none.fl_str_mv Racedo Galván, Jorge Mario
dc.contributor.researchgroup.es_CO.fl_str_mv microscopIA Research Group
dc.subject.keyword.none.fl_str_mv Artificial intelligence
Clinical research
Federated learning
topic Artificial intelligence
Clinical research
Federated learning
Aprendizaje automático (Inteligencia artificial)
Ingeniería
dc.subject.armarc.none.fl_str_mv Aprendizaje automático (Inteligencia artificial)
dc.subject.themes.es_CO.fl_str_mv Ingeniería
description Most 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, screening-diagnosis, 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 policymaking.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-06-22T21:52:00Z
dc.date.available.none.fl_str_mv 2022-06-22T21:52:00Z
dc.date.issued.none.fl_str_mv 2022-06-22
dc.type.es_CO.fl_str_mv Trabajo de grado - Pregrado
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/bachelorThesis
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dc.language.iso.es_CO.fl_str_mv eng
language eng
dc.rights.license.spa.fl_str_mv Attribution-NoDerivatives 4.0 Internacional
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dc.format.extent.es_CO.fl_str_mv 22 páginas
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dc.publisher.es_CO.fl_str_mv Universidad de los Andes
dc.publisher.program.es_CO.fl_str_mv Ingeniería Biomédica
dc.publisher.faculty.es_CO.fl_str_mv Facultad de Ingeniería
dc.publisher.department.es_CO.fl_str_mv Departamento de Ingeniería Biomédica
institution Universidad de los Andes
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