Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence?
Acute appendicitis in the pediatric population is a pathology of heterogeneous presentation that is currently diagnosed using various criteria or predictive scales, which have proven not to be sufficiently accurate to be standardized, however, methods have been created to establish a more accurate d...
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Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología
2024
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/med/article/view/44316 |
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I10-R327-article-443162024-04-24T19:00:41Z Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? Escala predictiva de apendicitis para menores de 4 años: ¿Es posible aplicar la inteligencia artificial? Escala preditiva de apendicite para crianças com menos de 4 anos: é possível aplicar a inteligência artificial? Arango Cárdenas, Dayhana Castrillón Lozano , Jorge Andrés Areiza Ocampo , Ximena artificial intelligence appendicitis pediatric inteligencia artificial apendicitis pediatría inteligência artificial apendicite Pediatria Acute appendicitis in the pediatric population is a pathology of heterogeneous presentation that is currently diagnosed using various criteria or predictive scales, which have proven not to be sufficiently accurate to be standardized, however, methods have been created to establish a more accurate diagnosis, an aspect that has been provided by artificial intelligence, which through different algorithms has the ability to show the patient's condition and the most appropriate intervention for this, thus reducing the rate of unnecessary interventions and therefore possible related complications. La apendicitis aguda en la población pediátrica es una patología de presentación heterogénea que es diagnósticada actualmente mediante diversos criterios o escalas predictivas, que han demostrado no ser lo suficientemente precisas para ser estandarizadas, sin embargo, se han creado métodos que permitan establecer un diagnóstico más preciso, aspecto que ha sido proporcionado por la inteligencia artificial, la cual mediante diferentes algoritmos cuenta con la capacidad de arrojar cuál es el estado del paciente y la intervención más adecuada para este, disminuyendo así la tasa de intervenciones inecesarias y por ende posibles complicaciones relacionadas. A apendicite aguda na população pediátrica é uma patologia de apresentação heterogénea que, atualmente, é diagnosticada através de vários critérios ou escalas preditivas, que se revelaram não suficientemente precisos para serem padronizados. No entanto, foram criados métodos para estabelecer um diagnóstico mais preciso, aspeto que tem sido proporcionado pela inteligência artificial, que através de diferentes algoritmos tem a capacidade de mostrar o estado do paciente e a intervenção mais adequada para o mesmo, reduzindo assim a taxa de intervenções desnecessárias e, consequentemente, as possíveis complicações relacionadas. Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología 2024-03-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion text/html application/pdf https://revistas.unc.edu.ar/index.php/med/article/view/44316 10.31053/1853.0605.v81.n1.44316 Revista de la Facultad de Ciencias Médicas de Córdoba.; Vol. 81 No. 1 (2024); 196-203 Revista de la Facultad de Ciencias Médicas de Córdoba; Vol. 81 Núm. 1 (2024); 196-203 Revista da Faculdade de Ciências Médicas de Córdoba; v. 81 n. 1 (2024); 196-203 1853-0605 0014-6722 10.31053/1853.0605.v81.n1 spa https://revistas.unc.edu.ar/index.php/med/article/view/44316/44741 https://revistas.unc.edu.ar/index.php/med/article/view/44316/44773 Derechos de autor 2024 Universidad Nacional de Córdoba http://creativecommons.org/licenses/by-nc/4.0 |
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Universidad Nacional de Córdoba |
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I-10 |
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R-327 |
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Revista de la Facultad de Ciencias Médicas de Córdoba |
| language |
Español |
| format |
Artículo revista |
| topic |
artificial intelligence appendicitis pediatric inteligencia artificial apendicitis pediatría inteligência artificial apendicite Pediatria |
| spellingShingle |
artificial intelligence appendicitis pediatric inteligencia artificial apendicitis pediatría inteligência artificial apendicite Pediatria Arango Cárdenas, Dayhana Castrillón Lozano , Jorge Andrés Areiza Ocampo , Ximena Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| topic_facet |
artificial intelligence appendicitis pediatric inteligencia artificial apendicitis pediatría inteligência artificial apendicite Pediatria |
| author |
Arango Cárdenas, Dayhana Castrillón Lozano , Jorge Andrés Areiza Ocampo , Ximena |
| author_facet |
Arango Cárdenas, Dayhana Castrillón Lozano , Jorge Andrés Areiza Ocampo , Ximena |
| author_sort |
Arango Cárdenas, Dayhana |
| title |
Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| title_short |
Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| title_full |
Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| title_fullStr |
Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| title_full_unstemmed |
Predictive appendicitis scale for children under 4 years of age : Is it possible to apply artificial intelligence? |
| title_sort |
predictive appendicitis scale for children under 4 years of age : is it possible to apply artificial intelligence? |
| description |
Acute appendicitis in the pediatric population is a pathology of heterogeneous presentation that is currently diagnosed using various criteria or predictive scales, which have proven not to be sufficiently accurate to be standardized, however, methods have been created to establish a more accurate diagnosis, an aspect that has been provided by artificial intelligence, which through different algorithms has the ability to show the patient's condition and the most appropriate intervention for this, thus reducing the rate of unnecessary interventions and therefore possible related complications. |
| publisher |
Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología |
| publishDate |
2024 |
| url |
https://revistas.unc.edu.ar/index.php/med/article/view/44316 |
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