Application of Artificial Intelligence Algorithms Within the Medical Context for Non-Specialized Users: the CARTIER-IA Platform
Autor:
García-Peñalvo, Francisco
; Vázquez-Ingelmo, Andrea
; García-Holgado, Alicia
; Sampedro-Gómez, Jesús
; Sánchez-Puente, Antonio
; Vicente-Palacios, Víctor
; Dorado-Díaz, P. Ignacio
; Sánchez, Pedro L.
Fecha:
06/2021Palabra clave:
Revista / editorial:
International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)Tipo de Ítem:
articleDirección web:
https://www.ijimai.org/journal/bibcite/reference/2949Resumen:
The use of advanced algorithms and models such as Machine Learning, Deep Learning and other related approaches of Artificial Intelligence have grown in their use given their benefits in different contexts. One of these contexts is the medical domain, as these algorithms can support disease detection, image segmentation and other multiple tasks. However, it is necessary to organize and arrange the different data resources involved in these scenarios and tackle the heterogeneity of data sources. This work presents the CARTIER-IA platform:
a platform for the management of medical data and imaging. The goal of this project focuses on providing a friendly and usable interface to organize structured data, to visualize and edit medical images, and to apply Artificial Intelligence algorithms on the stored resources. One of the challenges of the platform design is to ease these complex tasks in a way that non-AI-specialized users could benefit from the application of AI algorithms without further training. Two use cases of AI application within the platform are provided, as well as a heuristic evaluation to assess the usability of the first version of CARTIER-IA.
Year of Publication
2021
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
6
Issue
Regular Issue
Number
6
Number of Pages
46-53
Date Published
06/2021
ISSN Number
1989-1660
URL
https://www.ijimai.org/journal/sites/default/files/2021-05/ijimai_6_6_5.pdf
DOI
10.9781/ijimai.2021.05.005
DOI
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