2026-09-14T05:46:09Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1538242025-12-12T08:43:38Zcom_10366_4549com_10366_4512com_10366_3823col_10366_4550

Vázquez Ingelmo, Andrea García-Holgado, Alicia García-Peñalvo, Francisco J. Pérez-Sánchez, Pablo Antúnez-Muiños, Pablo Sánchez-Puente, Antonio Vicente-Palacios, Víctor Dorado-Díaz, Pedro Ignacio Sánchez Fernández, Pedro Luis 2023-12-05T19:07:31Z 2023-12-05T19:07:31Z 2023 0302-9743 http://hdl.handle.net/10366/153824 10.1007/978-3-031-42935-4_20 1611-3349 The prevalence of artificial intelligence (AI) in our daily lives is often exaggerated by the media, leading to a positive public perception while overlooking potential problems. In the field of medicine, it is crucial to educate future healthcare professionals on the advantages and disadvantages of AI and to emphasize the importance of creating fair, ethical, and reproducible models. The KoopaML platform was developed to provide an educational and user-friendly interface for inexperienced users to create AI pipelines. This study analyzes the quantitative and interaction data gathered from a usability test involving physicians from the University Hospital of Salamanca, with the aim of identifying new interaction paradigms to improve the platform’s usability. The results shown that the platform is difficult to learn for inexperienced users due to its contents related to AI. Following these results, a set of improvements are proposed for the next version of KoopaML, focusing on reducing the interactions needed to create the pipelines. eng http://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess Atribución-NoComercial-CompartirIgual 4.0 Internacional Information system Medical data management Artificial Intelligence Health platform HCI Usability SUS Are Textual Recommendations Enough? Guiding Physicians Toward the Design of Machine Learning Pipelines Through a Visual Platform info:eu-repo/semantics/article