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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34
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Item KoopaML: Application for receiving and processing DICOM images(CEUR-WS.org, 2023-12-05) Fraile-Sanchón, R.; Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.AI algorithms application to medical data has gained relevance due to their powerful benefits among different research tasks. However, medical data is heterogeneous and diverse, and these algorithms need technological support to tackle these data management challenges. KoopaML enables users to unify medical data, especially DICOM images and apply AI algorithms to them in a straightforward way through an online web application. This work presents a new feature in the KoopaML platform: a Machine Learning platform to assist non-expert users in defining and applying ML pipelines. The feature comprises the reception, storage, and management of DICOM images. These images are received through a connection with a PACS (Picture Archiving Communication System) system already configured by users on the platform and, after storing the images, it is possible to apply AI algorithms to them and make modifications or annotations.Item “Evolución”: Diseño e Implementación de Material Educativo Digital para Fortalecer Habilidades del Pensamiento Computacional(Sociedad de Educación del IEEE (Capítulo Español), 2018-03-21) Rico Lugo, M. J.; Basogain Olabe, X.; Moreno Niño, N.This article describes how an educational digital material supports the improvement of skills in the development of algorithms within Math problems, which belong to a part of an operative computational thinking, in students of the subject Logic Programming. This study reflects how students lack the fundamentals of Math and the algorithmic thinking required to solve the problems established in the educational digital material. The results show that doing a reiterative challenge help students not just to get the fundamentals of Math, but also to solve the algorithms used in the educational digital material, learning from the mistakes made.