Multi-Disease Explainable Deep Learning System for Automated Chest X-ray Screening
| UDC.coleccion | Investigación | |
| UDC.conferenceTitle | EUROCAST 2026 | |
| UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | |
| UDC.endPage | 232 | |
| UDC.grupoInv | Grupo de Visión Artificial e Recoñecemento de Patróns (VARPA) | |
| UDC.institutoCentro | INIBIC - Instituto de Investigacións Biomédicas de A Coruña | |
| UDC.startPage | 231 | |
| dc.contributor.author | Goyanes, Elena | |
| dc.contributor.author | Fernández Moreira, Breogán | |
| dc.contributor.author | Moura, Joaquim de | |
| dc.contributor.author | Novo Buján, Jorge | |
| dc.contributor.author | Ortega Hortas, Marcos | |
| dc.date.accessioned | 2026-09-02T08:44:17Z | |
| dc.date.available | 2026-09-02T08:44:17Z | |
| dc.date.issued | 2026-02 | |
| dc.description | Presentado en: EUROCAST 2026, 20th International Conference on Computer Aided Systems Theory Las Palmas de Gran Canaria, Spain, February 23- 27, 2026 | |
| dc.description.abstract | [Abstract]: This paper presents an explainable deep learning system for the simultaneous screening of multiple pulmonary diseases in chest Xrays. Ten state-of-the-art convolutional and transformer-based architectures were evaluated to identify the most effective model for multi-label classification, with the best-performing model achieving an average AUC of 0.841. The interpretability of the system was enhanced using Grad-CAM, providing visual explanations consistent with clinical findings. | |
| dc.description.sponsorship | This work was supported by Government of Spain through the research projects with [grant number PID2023-148913OB-I00] and [grant number PID2024-161024OB-I00], funded by MICIU/AEI/10.13039/501100011033 and by ERDF, EU; Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, Grupos de Referencia Competitiva, [grant number ED431C 2024/33], predoctoral grant [grant number ED481A-2023-152]. Also supported by the ISCIII under the grant [FORT23/00010] as part of the Programa FORTALECE of MICIU. | |
| dc.description.sponsorship | Xunta de Galicia; ED431C 2024/33 | |
| dc.description.sponsorship | Xunta de Galicia; ED481A-2023-152 | |
| dc.identifier.citation | E. Goyanes, B. Fernández-Moreira, J. de Moura, J. Novo, and M. Ortega, "Multi-Disease Explainable Deep Learning System for Automated Chest X-ray Screening", in Proc. 20th Int. Conf. on Computer Aided Systems Theory (EUROCAST 2026), Extended Abstracts, A. Espino-Sánchez, G. S. de Blasio, C. R. García, J. C. Rodríguez, M. Quesada-Ojeda, and A. Quesada-Arencibia, Eds., Las Palmas de Gran Canaria, Spain, 2026. | |
| dc.identifier.isbn | 978-84-09-81744-3 | |
| dc.identifier.uri | https://hdl.handle.net/2183/49131 | |
| dc.language.iso | eng | |
| dc.publisher | Universidad de Las Palmas de Gran Canaria | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PID2023-148913OB-I00/ES/IA CONFIABLE Y EXPLICABLE PARA EL DIAGNOSTICO POR IMAGEN MEDICA ASISTIDO POR ORDENADOR: NUEVOS AVANCES Y APLICACIONES | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2024-2027/PID2024-161024OB-I00/ES/APRENDIZAJE PROFUNDO DE SINTESIS DE IMAGENES Y ALINEAMIENTO MULTIVISTA PARA APROVECHAR DATOS NO ETIQUETADOS. APLICACIONES EN ANALISIS DE IMAGEN MEDICA/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/FORT23%2F00010/ES/ | |
| dc.relation.uri | https://eurocast2026.fulp.es/documents/Extended_Abstract_Book.pdf | |
| dc.rights | © 2026 IUCES Universidad de Las Palmas de Gran Canaria | |
| dc.rights.accessRights | embargoed access | |
| dc.subject | Chest X-ray | |
| dc.subject | Deep Learning | |
| dc.subject | Explainable AI | |
| dc.subject | Medical Image Processing | |
| dc.subject | Pulmonary Pathologies | |
| dc.title | Multi-Disease Explainable Deep Learning System for Automated Chest X-ray Screening | |
| dc.type | conference output | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 20509a9e-9f98-4198-baf6-dbc0e34686f9 | |
| relation.isAuthorOfPublication | 028dac6b-dd82-408f-bc69-0a52e2340a54 | |
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| relation.isAuthorOfPublication | 1fb98665-ea68-4cd3-a6af-83e6bb453581 | |
| relation.isAuthorOfPublication.latestForDiscovery | 20509a9e-9f98-4198-baf6-dbc0e34686f9 |
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