Addressing fairness in artificial intelligence for medical imaging

Autores
Ricci Lara, María Agustina; Echeveste, Rodrigo Sebastián; Ferrante, Enzo
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area and comment on the potential sources of biases, as well as the strategies available to mitigate them. Finally, we analyze the current state of the field, identifying strengths and highlighting areas of vacancy, challenges and opportunities that lie ahead.
Fil: Ricci Lara, María Agustina. Universidad Tecnológica Nacional; Argentina. Hospital Italiano. Departamento de Informática En Salud.; Argentina
Fil: Echeveste, Rodrigo Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Ferrante, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Materia
Fairness
Artificial Intelligence
Medical Imaging
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/213281
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Addressing fairness in artificial intelligence for medical imagingRicci Lara, María AgustinaEcheveste, Rodrigo SebastiánFerrante, EnzoFairnessArtificial IntelligenceMedical Imaginghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area and comment on the potential sources of biases, as well as the strategies available to mitigate them. Finally, we analyze the current state of the field, identifying strengths and highlighting areas of vacancy, challenges and opportunities that lie ahead.Fil: Ricci Lara, María Agustina. Universidad Tecnológica Nacional; Argentina. Hospital Italiano. Departamento de Informática En Salud.; ArgentinaFil: Echeveste, Rodrigo Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Ferrante, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaNature Research2022-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/213281Ricci Lara, María Agustina; Echeveste, Rodrigo Sebastián; Ferrante, Enzo; Addressing fairness in artificial intelligence for medical imaging; Nature Research; Nature Communications; 13; 1; 8-2022; 1-62041-1723CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41467-022-32186-3info:eu-repo/semantics/altIdentifier/doi/10.1038/s41467-022-32186-3info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:38:19Zoai:ri.conicet.gov.ar:11336/213281instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:38:19.655CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Addressing fairness in artificial intelligence for medical imaging
title Addressing fairness in artificial intelligence for medical imaging
spellingShingle Addressing fairness in artificial intelligence for medical imaging
Ricci Lara, María Agustina
Fairness
Artificial Intelligence
Medical Imaging
title_short Addressing fairness in artificial intelligence for medical imaging
title_full Addressing fairness in artificial intelligence for medical imaging
title_fullStr Addressing fairness in artificial intelligence for medical imaging
title_full_unstemmed Addressing fairness in artificial intelligence for medical imaging
title_sort Addressing fairness in artificial intelligence for medical imaging
dc.creator.none.fl_str_mv Ricci Lara, María Agustina
Echeveste, Rodrigo Sebastián
Ferrante, Enzo
author Ricci Lara, María Agustina
author_facet Ricci Lara, María Agustina
Echeveste, Rodrigo Sebastián
Ferrante, Enzo
author_role author
author2 Echeveste, Rodrigo Sebastián
Ferrante, Enzo
author2_role author
author
dc.subject.none.fl_str_mv Fairness
Artificial Intelligence
Medical Imaging
topic Fairness
Artificial Intelligence
Medical Imaging
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area and comment on the potential sources of biases, as well as the strategies available to mitigate them. Finally, we analyze the current state of the field, identifying strengths and highlighting areas of vacancy, challenges and opportunities that lie ahead.
Fil: Ricci Lara, María Agustina. Universidad Tecnológica Nacional; Argentina. Hospital Italiano. Departamento de Informática En Salud.; Argentina
Fil: Echeveste, Rodrigo Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Ferrante, Enzo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
description A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area and comment on the potential sources of biases, as well as the strategies available to mitigate them. Finally, we analyze the current state of the field, identifying strengths and highlighting areas of vacancy, challenges and opportunities that lie ahead.
publishDate 2022
dc.date.none.fl_str_mv 2022-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/213281
Ricci Lara, María Agustina; Echeveste, Rodrigo Sebastián; Ferrante, Enzo; Addressing fairness in artificial intelligence for medical imaging; Nature Research; Nature Communications; 13; 1; 8-2022; 1-6
2041-1723
CONICET Digital
CONICET
url http://hdl.handle.net/11336/213281
identifier_str_mv Ricci Lara, María Agustina; Echeveste, Rodrigo Sebastián; Ferrante, Enzo; Addressing fairness in artificial intelligence for medical imaging; Nature Research; Nature Communications; 13; 1; 8-2022; 1-6
2041-1723
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41467-022-32186-3
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41467-022-32186-3
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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