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Harnessing artificial intelligence for pediatric health: current trends and future opportunities

  • Jialin Wu
  • , Bonan Chen
  • , Kate Ching-Ching Chan
  • , Mingyu Liang
  • , Yang Lyu
  • , Peiyao Yu
  • , Tiejun Feng
  • , Fuda Xie
  • , Sifan Yu
  • , Fengbin Zhang
  • , Terry Cheuk-Fung Yip
  • , Wei Kang*
  • *Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

1 Citation (Scopus)

Abstract

Artificial Intelligence (AI) is transforming pediatric healthcare, offering novel opportunities for early diagnosis, personalized treatment, and more efficient clinical workflows. However, its integration into children's health faces significant challenges due to the unique developmental, biological, and ethical considerations involved. This review explores how AI, leveraging large-scale real-world data such as electronic health records (EHRs), can augment pediatric clinical decision-making, risk stratification, communication, and workflow under human oversight. We examine its current applications and potential to improve pediatric care in areas including disease diagnosis, prediction, prevention, and personalized treatment. Additionally, we evaluate the role of AI in accelerating pediatric drug discovery and in supporting global health and epidemic management for children. Despite these promising advancements, significant barriers, such as data scarcity, ethical dilemmas, and the interpretability challenges posed by “black box” models, must be addressed to enable widespread adoption.
Original languageEnglish
Article number115962
Number of pages35
JournaliScience
Volume29
Issue number6
Early online date30 Apr 2026
DOIs
Publication statusPublished - 19 Jun 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

User-Defined Keywords

  • Artificial intelligence
  • Children health
  • Deep learning
  • Machine learning
  • Pediatric

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