The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy

© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Detalles Bibliográficos
Autores: Frías, Marcos, Badosa Gallego, Maria del Carmen, Jiménez Mallebrera, Cecilia, Porta Pleite, Josep Maria|||0000-0002-5056-1717, Roldán Molina, Mónica
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/439469
Acceso en línea:https://hdl.handle.net/2117/439469
https://dx.doi.org/10.1016/j.compbiomed.2025.110610
Access Level:acceso abierto
Palabra clave:Rare diseases
Collagen VI
Artificial intelligence
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
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spelling The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophyFrías, MarcosBadosa Gallego, Maria del CarmenJiménez Mallebrera, CeciliaPorta Pleite, Josep Maria|||0000-0002-5056-1717Roldán Molina, MónicaRare diseasesCollagen VIArtificial intelligenceÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).The use of artificial intelligence (AI) techniques is significantly changing the analysis of medical images, accelerating and standardizing the diagnosis process. To train an AI model, however, a large dataset is typically required, especially when using the most powerful techniques. Therefore, not all specialties are taking advantage of AI techniques in the same way. For instance, they are seldomly used in areas such as the diagnosis of rare diseases since, due to their low prevalence, not enough data are typically available to train an AI model. In this paper, we address the use of AI techniques to diagnose a particular rare disease: Collagen VI-related Congenital Muscular Dystrophy from confocal microscopy images. We apply both classical machine learning and modern deep learning techniques and we show that, when using the appropriate data management and training procedures, one can successfully derive a highly-accurate classifier even with a limited amount of training data. Due to the generality of the explored techniques, this conclusion is likely to hold also for most of the rare diseases whose diagnosis relies on the examination of histological images.This work was supported by the European Union: HORIZON–MSCA–2022–DN, Improving BiomEdical diagnosis through LIGHT-based technologies and machine learning ‘‘BE-LIGHT’’ (GA n◦ 101119924 – BE-LIGHT); and the Instituto de Salud Carlos III, Spain (PI22/01382), FEDER (A way of making Europe) and Fundación Noelia.Peer ReviewedElsevier20252025-09-0120252025-07-25journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/439469https://dx.doi.org/10.1016/j.compbiomed.2025.110610reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/501100000780 HE 101119924 BE-LIGHT Improving BiomEdical diagnosis through LIGHT-based technologies and machine learningopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4394692026-05-27T15:37:01Z
dc.title.none.fl_str_mv The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
title The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
spellingShingle The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
Frías, Marcos
Rare diseases
Collagen VI
Artificial intelligence
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
title_short The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
title_full The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
title_fullStr The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
title_full_unstemmed The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
title_sort The artificial intelligence challenge in rare disease diagnosis: a case study on collagen VI muscular dystrophy
dc.creator.none.fl_str_mv Frías, Marcos
Badosa Gallego, Maria del Carmen
Jiménez Mallebrera, Cecilia
Porta Pleite, Josep Maria|||0000-0002-5056-1717
Roldán Molina, Mónica
author Frías, Marcos
author_facet Frías, Marcos
Badosa Gallego, Maria del Carmen
Jiménez Mallebrera, Cecilia
Porta Pleite, Josep Maria|||0000-0002-5056-1717
Roldán Molina, Mónica
author_role author
author2 Badosa Gallego, Maria del Carmen
Jiménez Mallebrera, Cecilia
Porta Pleite, Josep Maria|||0000-0002-5056-1717
Roldán Molina, Mónica
author2_role author
author
author
author
dc.subject.none.fl_str_mv Rare diseases
Collagen VI
Artificial intelligence
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
topic Rare diseases
Collagen VI
Artificial intelligence
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
description © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-09-01
2025
2025-07-25
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/439469
https://dx.doi.org/10.1016/j.compbiomed.2025.110610
url https://hdl.handle.net/2117/439469
https://dx.doi.org/10.1016/j.compbiomed.2025.110610
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/501100000780 HE 101119924 BE-LIGHT Improving BiomEdical diagnosis through LIGHT-based technologies and machine learning
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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