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Profiling Atopic Dermatitis Patients Using Decision Tree Classifiers to Anticipate Dupilumab Response

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Progress in Artificial Intelligence (EPIA 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14968))

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Abstract

Atopic dermatitis is a common disease that severely impairs patients’ quality of life. In recent years, novel targeted therapies have emerged as an alternative to conventional treatments for the most serious cases of the disease. Dupilumab is one such medication that offers many patients a chance to improve their condition. Despite its high efficacy rate, not all patients improve after therapy. In addition, the drug is expensive and can lead to significant side effects. This paper defines a methodology for patient profiling based on the expected response to dupilumab treatment. Based on various scenarios, we built decision trees that are able to distinguish patients who respond to dupilumab treatment from those who do not, achieving acceptable values for specificity, sensitivity and accuracy. Once properly validated, the rules associated with these decision trees can be used as a tool to support medical decision-making and contribute to an initial screening of patients even before treatment.

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Notes

  1. 1.

    Eczema Area and Severity Index.

  2. 2.

    https://www.ncbi.nlm.nih.gov/geo/

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Acknowledgements

This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, and the PhD grant: 2022.12728.BD.

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Authors and Affiliations

  1. Algoritmi R&D Centre/LASI, University of Minho, Campus of Gualtar, 4710-057, Braga, Portugal

    Ana Duarte & Orlando Belo

Authors
  1. Ana Duarte
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  2. Orlando Belo
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Correspondence to Ana Duarte .

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Editors and Affiliations

  1. University of Minho, Braga, Portugal

    Manuel Filipe Santos

  2. University of Minho, Braga, Portugal

    José Machado

  3. University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Minho, Braga, Portugal

    Paulo Cortez

  5. Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal

    Pedro Miguel Moreira

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Duarte, A., Belo, O. (2025). Profiling Atopic Dermatitis Patients Using Decision Tree Classifiers to Anticipate Dupilumab Response. In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14968. Springer, Cham. https://doi.org/10.1007/978-3-031-73500-4_2

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  • DOI: https://doi.org/10.1007/978-3-031-73500-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-73499-1

  • Online ISBN: 978-3-031-73500-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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