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Communication Dans Un Congrès Année : 2022

An evolutionary approach to the discretization of gene expression profiles to predict the severity of COVID-19

Résumé

In this work, we propose to use a state-of-the-art evolutionary algorithm to set the discretization thresholds for gene expression profiles, using feedback from a classifier in order to maximize the accuracy of the predictions based on the discretized gene expression levels, while at the same time minimizing the number of different profiles obtained, to ease the understanding of the expert. The methodology is applied to a dataset containing COVID-19 patients that developed either mild or severe symptoms. The results show that the evolutionary approach performs better than a traditional discretization based on statistical analysis, and that it does preserve the sense-making necessary for practitioners to trust the results.
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Dates et versions

hal-03818208 , version 1 (17-10-2022)

Identifiants

Citer

Nisrine Mouhrim, Alberto Tonda, Itzel Rodríguez-Guerra, Aletta D Kraneveld, Alejandro Lopez Rincon. An evolutionary approach to the discretization of gene expression profiles to predict the severity of COVID-19. GECCO 2022, Jul 2022, Boston, United States. ⟨10.1145/3520304.3529001⟩. ⟨hal-03818208⟩
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