An evolutionary approach to the discretization of gene expression profiles to predict the severity of COVID-19
2022 Genetic and Evolutionary Computation Conference, GECCO 2022
; : 731-734, 2022.
Article
in English
| Scopus | ID: covidwho-2020379
ABSTRACT
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. © 2022 Owner/Author.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
2022 Genetic and Evolutionary Computation Conference, GECCO 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS