Patología digital en la era de la inteligencia artificial y su impacto sobre el diagnóstico y pronóstico del mastocitoma cutáneo canino
| dc.contributor.advisor | Montoya Flórez, Luis Mauricio | |
| dc.contributor.author | Alfaro Campo, Ronaldo Edu | |
| dc.date.accessioned | 2025-09-11T12:50:41Z | |
| dc.date.available | 2025-09-11T12:50:41Z | |
| dc.date.issued | 2025 | |
| dc.description | ilustraciones (principalmente a color), diagramas, gráficos | spa |
| dc.description.abstract | La patología digital y la inteligencia artificial (IA) han revolucionado el diagnóstico de enfermedades en medicina veterinaria, permitiendo análisis más precisos y reproducibles. En el caso del mastocitoma cutáneo canino (cMCT), una de las neoplasias más comunes en perros, la aplicación de modelos de IA ha demostrado mejorar la detección y clasificación de estos tumores. Sin embargo, persisten desafíos en la implementación clínica de estas herramientas, como la estandarización de métodos y la variabilidad interobservador. Este estudio realiza una revisión sistemática y metaanálisis sobre la eficacia de la IA en la patología digital aplicada al cMCT. Se analizaron estudios publicados entre 2018 y 2024, evaluando sensibilidad, especificidad, concordancia diagnóstica y sesgos de publicación. Los resultados indicaron que los modelos de IA mejoran significativamente la precisión diagnóstica en comparación con la evaluación histopatológica tradicional. A pesar de la heterogeneidad entre estudios, la evidencia sugiere que la IA tiene un alto potencial para optimizar la identificación y clasificación de mastocitomas cutáneos. Se requieren más investigaciones para mejorar la generalización de los modelos y su implementación en la práctica clínica (Texto tomado de la fuente) | spa |
| dc.description.abstract | Digital pathology in the era of artificial intelligence and its impact on the diagnosis and prognosis of canine cutaneous mast cell tumor. Digital pathology and artificial intelligence (AI) have revolutionized disease diagnosis inveterinary medicine, enabling more precise and reproducible analyses. In the case of canine cutaneous mast cell tumor, one of the most common neoplasms in dogs, AI models have demonstrated improved detection and classification capabilities. However, challenges remain in the clinical implementation of these tools, including standardization of methods and interobserver variability. This study presents a systematic review and meta-analysis on the effectiveness of AI in digital pathology applied to canine cutaneous mast cell tumors. Studies published between 2018 and 2024 were analyzed, evaluating sensitivity, specificity, diagnostic agreement, and publication bias. The results indicated that AI models significantly improve diagnostic accuracy compared to traditional histopathological evaluation. Despite heterogeneity among studies, the evidence suggests that AI holds great potential for optimizing the identification and classification of cutaneous mast cell tumors. Further research is needed to enhance model generalization and its implementation in clinical practice. | eng |
| dc.description.degreelevel | Especialización | spa |
| dc.description.degreename | Especialista en Anatomopatología Veterinaria | spa |
| dc.description.methods | Este estudio se realizó siguiendo la metodología PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) para garantizar la transparencia y rigor en la revisión sistemática y el metaanálisis. Para ello, el protocolo detallado establecido en PRISMA incluyó la definición de la pregunta de investigación, la búsqueda de literatura, los criterios de inclusión y exclusión, y el uso de listas de verificación para la selección, caracterización, evaluación metodológica y extracción de datos (Page et al., 2021). | spa |
| dc.description.researcharea | Patología Veterinaria | spa |
| dc.format.extent | xiv, 18 páginas | |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.instname | Universidad Nacional de Colombia | spa |
| dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia | spa |
| dc.identifier.repourl | https://repositorio.unal.edu.co/ | spa |
| dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/88711 | |
| dc.language.iso | spa | spa |
| dc.publisher | Universidad Nacional de Colombia | spa |
| dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá | spa |
| dc.publisher.faculty | Facultad de Medicina Veterinaria y de Zootecnia | spa |
| dc.publisher.place | Bogotá | |
| dc.publisher.program | Bogotá - Medicina Veterinaria y de Zootecnia - Especialidad en Anatomopatología Veterinaria | spa |
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| dc.relation.references | Kiupel, M., Webster, J. D., Bailey, K. L., Best, S., DeLay, J., Detrisac, C. J., Fitzgerald, S. D., Gamble, D., Ginn, P. E., Goldschmidt, M. H., Hendrick, M. J., Howerth, E. W., Janovitz, E. B., Langohr, I., Lenz, S. D., Lipscomb, T. P., Miller, M. A., Misdorp, W., Moroff, S., … Miller, R. (2011). Proposal of a 2-Tier Histologic Grading System for Canine Cutaneous Mast Cell Tumors to More Accurately Predict Biological Behavior. Veterinary Pathology, 48(1), 147–155. https://doi.org/10.1177/0300985810386469 | |
| dc.relation.references | Kok, M. K., Chambers, J. K., Tsuboi, M., Nishimura, R., Tsujimoto, H., Uchida, K., & Nakayama, H. (2019). Retrospective study of canine cutaneous tumors in Japan, 2008–2017. Journal of Veterinary Medical Science, 81(8), 1133–1143. https://doi.org/10.1292/jvms.19-0248 | |
| dc.relation.references | Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60–88. https://doi.org/10.1016/j.media.2017.07.005 | |
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| dc.relation.references | Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. En The BMJ. https://doi.org/10.1136/bmj.n71 | |
| dc.relation.references | Patnaik, A. K., Ehler, W. J., & MacEwen, E. G. (1984). Canine Cutaneous Mast Cell Tumor: Morphologic Grading and Survival Time in 83 Dogs. Veterinary Pathology, 21(5), 469–474. https://doi.org/10.1177/030098588402100503 | |
| dc.relation.references | Porwit, A., McCullough, J., & Erber, W. E. (2011). Blood and Bone Marrow Pathology. Elsevier. https://doi.org/10.1016/C2009-0-52942-X | |
| dc.relation.references | Puget, C., Ganz, J., Ostermaier, J., Konrad, T., Parlak, E., Bertram, C. A., Kiupel, M., Breininger, K., Aubreville, M., & Klopfleisch, R. (2024). Deep Learning model predicts the c-Kit-11 mutational status of canine cutaneous mast cell tumors by HE stained histological slides. https://doi.org/https://doi.org/10.1177/03009858241286806 | |
| dc.relation.references | Rashidi, H. H., Tran, N. K., Betts, E. V., Howell, L. P., & Green, R. (2019). Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods. Academic Pathology, 6, 2374289519873088. https://doi.org/10.1177/2374289519873088 | |
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| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.license | Reconocimiento 4.0 Internacional | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 630 - Agricultura y tecnologías relacionadas::636 - Producción animal | spa |
| dc.subject.lemb | Patología veterinaria | spa |
| dc.subject.lemb | Veterinary pathology | eng |
| dc.subject.lemb | Medicina veterinaria | spa |
| dc.subject.lemb | Veterinary Medicine | eng |
| dc.subject.lemb | Telepatología | spa |
| dc.subject.lemb | Telepathology | eng |
| dc.subject.proposal | Cáncer | spa |
| dc.subject.proposal | Inteligencia artificial | spa |
| dc.subject.proposal | Mastocitoma | spa |
| dc.subject.proposal | WSI | |
| dc.subject.proposal | Cancer | eng |
| dc.subject.proposal | Artificial intelligence | eng |
| dc.subject.proposal | Mast cell tumor | eng |
| dc.title | Patología digital en la era de la inteligencia artificial y su impacto sobre el diagnóstico y pronóstico del mastocitoma cutáneo canino | spa |
| dc.title.translated | Digital pathology in the era of artificial intelligence and its impact on the diagnosis and prognosis of canine cutaneous mast cell tumor | eng |
| dc.type | Trabajo de grado - Especialización | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.content | Text | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
| dc.type.redcol | http://purl.org/redcol/resource_type/TP | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dcterms.audience.professionaldevelopment | Público general | spa |
| oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |