An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19

Nisrine Mouhrim; Alberto Tonda; Itzel Rodríguez-Guerra; Aletta D. Kraneveld; Alejandro Lopez Rincon

doi:10.1145/3520304.3529001

An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19

Nisrine Mouhrim, Alberto Tonda, Itzel Rodríguez-Guerra, Aletta D. Kraneveld, Alejandro Lopez Rincon

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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.

Original language	English
Title of host publication	GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery, Inc
Pages	731–734
Number of pages	4
ISBN (Electronic)	9781450392686
ISBN (Print)	9781450392686
DOIs	https://doi.org/10.1145/3520304.3529001
Publication status	Published - 9 Jul 2022
Externally published	Yes

Publication series

Name	GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference

Keywords

covid-19
discretization
evolutionary optimization
gene expression profiles
prognosis

Access to Document

10.1145/3520304.3529001

Cite this

Mouhrim, N., Tonda, A., Rodríguez-Guerra, I., Kraneveld, A. D., & Rincon, A. L. (2022). An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 731–734). (GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference). Association for Computing Machinery, Inc. https://doi.org/10.1145/3520304.3529001

Mouhrim, Nisrine ; Tonda, Alberto ; Rodríguez-Guerra, Itzel et al. / An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19. GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. New York, NY, USA : Association for Computing Machinery, Inc, 2022. pp. 731–734 (GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference).

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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.",

keywords = "covid-19, discretization, evolutionary optimization, gene expression profiles, prognosis",

author = "Nisrine Mouhrim and Alberto Tonda and Itzel Rodr{\'i}guez-Guerra and Kraneveld, {Aletta D.} and Rincon, {Alejandro Lopez}",

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Mouhrim, N, Tonda, A, Rodríguez-Guerra, I, Kraneveld, AD & Rincon, AL 2022, An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19. in GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, Inc, New York, NY, USA, pp. 731–734. https://doi.org/10.1145/3520304.3529001

An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19. / Mouhrim, Nisrine; Tonda, Alberto; Rodríguez-Guerra, Itzel et al.
GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. New York, NY, USA: Association for Computing Machinery, Inc, 2022. p. 731–734 (GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Kraneveld, Aletta D.

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AB - 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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Mouhrim N, Tonda A, Rodríguez-Guerra I, Kraneveld AD, Rincon AL. An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference. New York, NY, USA: Association for Computing Machinery, Inc. 2022. p. 731–734. (GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference). doi: 10.1145/3520304.3529001

An Evolutionary Approach to the Discretization of Gene Expression Profiles to Predict the Severity of COVID-19

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