Cargando…

A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population

In recent years, numerous dermatological image databases have been published to make possible the development and validation of artificial intelligence-based technologies to support healthcare professionals in the diagnosis of skin diseases. However, the generation of these datasets confined to cert...

Descripción completa

Detalles Bibliográficos
Autores principales: Ricci Lara, María Agustina, Rodríguez Kowalczuk, María Victoria, Lisa Eliceche, Maite, Ferraresso, María Guillermina, Luna, Daniel Roberto, Benitez, Sonia Elizabeth, Mazzuoccolo, Luis Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584927/
https://www.ncbi.nlm.nih.gov/pubmed/37853053
http://dx.doi.org/10.1038/s41597-023-02630-0
_version_ 1785122844747759616
author Ricci Lara, María Agustina
Rodríguez Kowalczuk, María Victoria
Lisa Eliceche, Maite
Ferraresso, María Guillermina
Luna, Daniel Roberto
Benitez, Sonia Elizabeth
Mazzuoccolo, Luis Daniel
author_facet Ricci Lara, María Agustina
Rodríguez Kowalczuk, María Victoria
Lisa Eliceche, Maite
Ferraresso, María Guillermina
Luna, Daniel Roberto
Benitez, Sonia Elizabeth
Mazzuoccolo, Luis Daniel
author_sort Ricci Lara, María Agustina
collection PubMed
description In recent years, numerous dermatological image databases have been published to make possible the development and validation of artificial intelligence-based technologies to support healthcare professionals in the diagnosis of skin diseases. However, the generation of these datasets confined to certain countries as well as the lack of demographic information accompanying the images, prevents having a real knowledge of in which populations these models could be used. Consequently, this hinders the translation of the models to the clinical setting. This has led the scientific community to encourage the detailed and transparent reporting of the databases used for artificial intelligence developments, as well as to promote the formation of genuinely international databases that can be representative of the world population. Through this work, we seek to provide details of the processing stages of the first public database of dermoscopy and clinical images created in a hospital in Argentina. The dataset comprises 1,616 images corresponding to 1,246 unique lesions collected from 623 patients.
format Online
Article
Text
id pubmed-10584927
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-105849272023-10-20 A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population Ricci Lara, María Agustina Rodríguez Kowalczuk, María Victoria Lisa Eliceche, Maite Ferraresso, María Guillermina Luna, Daniel Roberto Benitez, Sonia Elizabeth Mazzuoccolo, Luis Daniel Sci Data Data Descriptor In recent years, numerous dermatological image databases have been published to make possible the development and validation of artificial intelligence-based technologies to support healthcare professionals in the diagnosis of skin diseases. However, the generation of these datasets confined to certain countries as well as the lack of demographic information accompanying the images, prevents having a real knowledge of in which populations these models could be used. Consequently, this hinders the translation of the models to the clinical setting. This has led the scientific community to encourage the detailed and transparent reporting of the databases used for artificial intelligence developments, as well as to promote the formation of genuinely international databases that can be representative of the world population. Through this work, we seek to provide details of the processing stages of the first public database of dermoscopy and clinical images created in a hospital in Argentina. The dataset comprises 1,616 images corresponding to 1,246 unique lesions collected from 623 patients. Nature Publishing Group UK 2023-10-18 /pmc/articles/PMC10584927/ /pubmed/37853053 http://dx.doi.org/10.1038/s41597-023-02630-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Ricci Lara, María Agustina
Rodríguez Kowalczuk, María Victoria
Lisa Eliceche, Maite
Ferraresso, María Guillermina
Luna, Daniel Roberto
Benitez, Sonia Elizabeth
Mazzuoccolo, Luis Daniel
A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title_full A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title_fullStr A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title_full_unstemmed A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title_short A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population
title_sort dataset of skin lesion images collected in argentina for the evaluation of ai tools in this population
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584927/
https://www.ncbi.nlm.nih.gov/pubmed/37853053
http://dx.doi.org/10.1038/s41597-023-02630-0
work_keys_str_mv AT riccilaramariaagustina adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT rodriguezkowalczukmariavictoria adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT lisaelicechemaite adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT ferraressomariaguillermina adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT lunadanielroberto adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT benitezsoniaelizabeth adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT mazzuoccololuisdaniel adatasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT riccilaramariaagustina datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT rodriguezkowalczukmariavictoria datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT lisaelicechemaite datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT ferraressomariaguillermina datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT lunadanielroberto datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT benitezsoniaelizabeth datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation
AT mazzuoccololuisdaniel datasetofskinlesionimagescollectedinargentinafortheevaluationofaitoolsinthispopulation