Cases of artificial intelligence applications for pneumonia detection in Peruvian health care institutions

• Autores: Ayma Pumainca, Juan Fidel, Carranza Dávila , Williams, Zacarias Vilca, Brayams Jhonatan, Fernández Altamirano, Edgardo Joaquín, Escobedo Bailon, Frank Edmundo
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Nacional Tecnológica de Lima Sur
• Repositorio: UNTL-Biotech
• Lenguaje: español
• OAI Identifier: oai:ojs2.localhost:article/137
• Enlace del recurso: https://revistas.untels.edu.pe/index.php/files/article/view/137
• Nivel de acceso: acceso abierto
• Materia: Sistema informático; tecnologías móviles; valor comercial; tecnologías de información

This article is the result of an exhaustive review of several cases of artificial intelligence (AI) application in Peruvian health institutions for pneumonia detection. These studies cover a variety of research approaches, from the development of AI-based systems to the evaluation of specific algorithms and the implementation of technological tools in clinical settings. In terms of research, it is noted that some studies focus on the design and implementation of complete AI-based systems using convolutional neural network algorithms to improve diagnostic accuracy and others focus on the evaluation of specific algorithms, such as ResNet50 or VGG16, comparing their performance in identifying pneumonia in radiographic images. In addition, research that proposes novel protocols for data acquisition, such as the transformation of sounds of respiratory diseases into images for subsequent analysis with convolutional neural networks, is highlighted. Also mentioned are initiatives that develop mobile and web applications to facilitate the visualization of results by physicians and improve the efficiency of the diagnostic process.