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AI-Enhanced Decision-Making in Childhood Obesity Interventions

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Decision Sciences (DSA ISC 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14778))

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Abstract

Childhood obesity represents a global public health challenge. This study employs artificial intelligence (AI) to enhance decision-making in pediatric interventions against obesity. A predictive model was developed using data from children participating in an obesity intervention program at the Pediatric Service of the Elx-Crevillent Health Department to identify which type of patient achieves a successful outcome after a standard obesity intervention. The results demonstrate the potential of AI to improve personalized healthcare and optimize resources in combating childhood obesity, specifically in defining which patients may benefit from standard procedures and which patients may require additional resources to achieve improvements. This pilot research contributes to a deeper understanding of the factors related to childhood obesity and lays the groundwork for future AI-driven innovations in pediatric health.

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Acknowledgments

This work has been supported by the Investigo Program of the Generalitat Valenciana (INVEST/2023/304) and the UNISALUT program of Fundaciö per al Foment de la Investigaciö Sanitária i Biomèdica de la Comunitat Valenciana (FISABIO) and Universitat Politècnica de València (POLISABIO22_AP06).

Author information

Authors and Affiliations

  1. Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València, Ferrandiz y Carbonell, s/n, 03802, Alcoy, Spain

    Raquel Soriano-Gonzalez, Noelia Fuster & Elena Perez-Bernabeu

  2. Department of Pediatrics, University Hospital Vinalopö, Elche, Spain

    Gonzalo Ros-Cervera

Authors
  1. Raquel Soriano-Gonzalez
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  2. Noelia Fuster
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  3. Elena Perez-Bernabeu
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  4. Gonzalo Ros-Cervera
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Corresponding author

Correspondence to Raquel Soriano-Gonzalez .

Editor information

Editors and Affiliations

  1. Universidad Politécnica de Valencia, Valencia, Spain

    Angel A. Juan

  2. Public University of Navarre, Pamplona, Spain

    Javier Faulin

  3. ESADE Business School, Sant Cugat, Spain

    David Lopez-Lopez

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Soriano-Gonzalez, R., Fuster, N., Perez-Bernabeu, E., Ros-Cervera, G. (2025). AI-Enhanced Decision-Making in Childhood Obesity Interventions. In: Juan, A.A., Faulin, J., Lopez-Lopez, D. (eds) Decision Sciences. DSA ISC 2024. Lecture Notes in Computer Science, vol 14778. Springer, Cham. https://doi.org/10.1007/978-3-031-78238-1_13

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  • DOI: https://doi.org/10.1007/978-3-031-78238-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-78237-4

  • Online ISBN: 978-3-031-78238-1

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