Artículo
Addressing fairness in artificial intelligence for medical imaging
Fecha de publicación:
08/2022
Editorial:
Nature Research
Revista:
Nature Communications
ISSN:
2041-1723
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area and comment on the potential sources of biases, as well as the strategies available to mitigate them. Finally, we analyze the current state of the field, identifying strengths and highlighting areas of vacancy, challenges and opportunities that lie ahead.
Palabras clave:
Fairness
,
Artificial Intelligence
,
Medical Imaging
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Articulos(SINC(I))
Articulos de INST. DE INVESTIGACION EN SEÑALES, SISTEMAS E INTELIGENCIA COMPUTACIONAL
Articulos de INST. DE INVESTIGACION EN SEÑALES, SISTEMAS E INTELIGENCIA COMPUTACIONAL
Citación
Ricci Lara, María Agustina; Echeveste, Rodrigo Sebastián; Ferrante, Enzo; Addressing fairness in artificial intelligence for medical imaging; Nature Research; Nature Communications; 13; 1; 8-2022; 1-6
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