Towards explainable artificial intelligence for the leukemia subtype recognition

Rocio Ochoa-Montiel, Gustavo Olague, Humberto Sossa

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In this work, we provide a solution to the leukemia subtype recognition problem. Most approaches used for solving a variety of pattern recognition problems have a drawback: in general, they lack explainability. In this paper, we provide a solution for facing this situation. We describe a model whose stages allow deriving knowledge for solving the leukemia subtype recognition problem, are intelligible for the user. Results show that multiclass recognition is achieved from the solutions obtained by the model through multiple runs.

Idioma originalInglés
Título de la publicación alojada2021 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728188645
DOI
EstadoPublicada - 2021
Evento2021 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2021 - Temuco, Chile
Duración: 2 nov 20214 nov 2021

Serie de la publicación

Nombre2021 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2021

Conferencia

Conferencia2021 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2021
País/TerritorioChile
CiudadTemuco
Período2/11/214/11/21

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