Artificial intelligence for the identification of pediatric pneumonia in X rays

• Autores: Espinoza-Portilla, Elizabeth, Henríquez-Suárez, Milagro, Cilloniz , Catia
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo
• Repositorio: Revista del Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo
• Lenguaje: español
• OAI Identifier: oai:cmhnaaa_ojs_cmhnaaa.cmhnaaa.org.pe:article/2671
• Enlace del recurso: https://cmhnaaa.org.pe/ojs/index.php/rcmhnaaa/article/view/2671
• Nivel de acceso: acceso abierto
• Materia: Neumonía; radiografía; Pediatría; Inteligencia Artificial; Ética; Perú; Pneumonia; Radiography; Pediatrics; Artificial Intelligence; Ethics; Peru

The aim of this special article is to describe the role of artificial intelligence in the identification of pediatric pneumonia applied to chest X-rays, summarizing and analyzing the most relevant evidence and recent advancements. We also discuss its implications for improving diagnosis in areas with a shortage of specialists. Artificial intelligence offers great potential for enhancing the categorization of pediatric pneumonia in chest X-rays, especially in resource-limited regions. However, its success depends on the quality of the data, physicians' trust in the results, and the implementation of appropriate ethical and safety frameworks. While further research and the development of effective integration strategies are needed, artificial intelligence could play a crucial role in the global fight against childhood pneumonia.