A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7
Descripción del Articulo
Dental cavities represent a significant global health challenge, particularly in low-and middle-income countries, where early detection and diagnosis can substantially improve clinical outcomes. This study presents the development of a mobile application that utilizes YOLOv7 to detect early carious...
Autores: | , , |
---|---|
Formato: | artículo |
Fecha de Publicación: | 2025 |
Institución: | Universidad Peruana de Ciencias Aplicadas |
Repositorio: | UPC-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/686656 |
Enlace del recurso: | http://hdl.handle.net/10757/686656 |
Nivel de acceso: | acceso abierto |
Materia: | dental diagnosis intraoral images mobile application pre-carious lesions YOLOv7 |
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repository_id_str |
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dc.title.es_PE.fl_str_mv |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
title |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
spellingShingle |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 Huertas, William dental diagnosis intraoral images mobile application pre-carious lesions YOLOv7 |
title_short |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
title_full |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
title_fullStr |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
title_full_unstemmed |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
title_sort |
A Mobile Application for the Detection of Pre-Carious Lesions in Peruvian Patients based on YOLOv7 |
author |
Huertas, William |
author_facet |
Huertas, William Artica, Kevin Wong, Lenis |
author_role |
author |
author2 |
Artica, Kevin Wong, Lenis |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Huertas, William Artica, Kevin Wong, Lenis |
dc.subject.es_PE.fl_str_mv |
dental diagnosis intraoral images mobile application pre-carious lesions YOLOv7 |
topic |
dental diagnosis intraoral images mobile application pre-carious lesions YOLOv7 |
description |
Dental cavities represent a significant global health challenge, particularly in low-and middle-income countries, where early detection and diagnosis can substantially improve clinical outcomes. This study presents the development of a mobile application that utilizes YOLOv7 to detect early carious lesions on intraoral images, intending to provide dental professionals with a tool for timely diagnosis and intervention. The research was carried out in three key phases: analysis of YOLOv7, system development, and validation. The application was trained in a real clinical environment in Peru in collaboration with two independent dentists and their patients in two private clinics. Intraoral images were collected and processed from 40 participants, ensuring complete adherence to the ethical and privacy standards required for clinical studies. The experimental results demonstrated that the application achieved an average accuracy of 94%, with both accuracy and Positive Predictive Value (PPV) exceeding 90% in most cases. The results demonstrated consistent diagnostic accuracy and efficiency, validating the application's performance. Patient surveys reflected high satisfaction, with average scores of 4.4 for usability, 4.2 for efficiency, and 4.6 for functionality. Similarly, dentists rated the usability, functionality, and efficiency of the application with average scores of 4.5. These findings highlight the potential of the application to improve clinical workflows and accuracy in detecting early carious lesions. |
publishDate |
2025 |
dc.date.accessioned.none.fl_str_mv |
2025-09-16T05:04:57Z |
dc.date.available.none.fl_str_mv |
2025-09-16T05:04:57Z |
dc.date.issued.fl_str_mv |
2025-04-01 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
dc.identifier.issn.none.fl_str_mv |
22414487 |
dc.identifier.doi.none.fl_str_mv |
10.48084/etasr.8955 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10757/686656 |
dc.identifier.eissn.none.fl_str_mv |
17928036 |
dc.identifier.journal.es_PE.fl_str_mv |
Engineering Technology and Applied Science Research |
dc.identifier.eid.none.fl_str_mv |
2-s2.0-105003240959 |
dc.identifier.scopusid.none.fl_str_mv |
SCOPUS_ID:105003240959 |
dc.identifier.isni.none.fl_str_mv |
0000 0001 2196 144X |
identifier_str_mv |
22414487 10.48084/etasr.8955 17928036 Engineering Technology and Applied Science Research 2-s2.0-105003240959 SCOPUS_ID:105003240959 0000 0001 2196 144X |
url |
http://hdl.handle.net/10757/686656 |
dc.language.iso.es_PE.fl_str_mv |
eng |
language |
eng |
dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.*.fl_str_mv |
Attribution 4.0 International |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
dc.format.es_PE.fl_str_mv |
application/pdf |
dc.publisher.es_PE.fl_str_mv |
Dr D. Pylarinos |
dc.source.es_PE.fl_str_mv |
Repositorio Academico - UPC Universidad Peruana de Ciencias Aplicadas (UPC) |
dc.source.none.fl_str_mv |
reponame:UPC-Institucional instname:Universidad Peruana de Ciencias Aplicadas instacron:UPC |
instname_str |
Universidad Peruana de Ciencias Aplicadas |
instacron_str |
UPC |
institution |
UPC |
reponame_str |
UPC-Institucional |
collection |
UPC-Institucional |
dc.source.journaltitle.none.fl_str_mv |
Engineering Technology and Applied Science Research |
dc.source.volume.none.fl_str_mv |
15 |
dc.source.issue.none.fl_str_mv |
2 |
dc.source.beginpage.none.fl_str_mv |
21270 |
dc.source.endpage.none.fl_str_mv |
21278 |
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2d68a0130417120cc3e0a38a0a36b11250085cccf2266851d31df3628892265bed9500f1524a3bbf68b7e2680e1ab2f7ba0bfd500Huertas, WilliamArtica, KevinWong, Lenis2025-09-16T05:04:57Z2025-09-16T05:04:57Z2025-04-012241448710.48084/etasr.8955http://hdl.handle.net/10757/68665617928036Engineering Technology and Applied Science Research2-s2.0-105003240959SCOPUS_ID:1050032409590000 0001 2196 144XDental cavities represent a significant global health challenge, particularly in low-and middle-income countries, where early detection and diagnosis can substantially improve clinical outcomes. This study presents the development of a mobile application that utilizes YOLOv7 to detect early carious lesions on intraoral images, intending to provide dental professionals with a tool for timely diagnosis and intervention. The research was carried out in three key phases: analysis of YOLOv7, system development, and validation. The application was trained in a real clinical environment in Peru in collaboration with two independent dentists and their patients in two private clinics. Intraoral images were collected and processed from 40 participants, ensuring complete adherence to the ethical and privacy standards required for clinical studies. The experimental results demonstrated that the application achieved an average accuracy of 94%, with both accuracy and Positive Predictive Value (PPV) exceeding 90% in most cases. The results demonstrated consistent diagnostic accuracy and efficiency, validating the application's performance. Patient surveys reflected high satisfaction, with average scores of 4.4 for usability, 4.2 for efficiency, and 4.6 for functionality. Similarly, dentists rated the usability, functionality, and efficiency of the application with average scores of 4.5. These findings highlight the potential of the application to improve clinical workflows and accuracy in detecting early carious lesions.Revisión por paresapplication/pdfengDr D. 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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).