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

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Authors: 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
Cited by: 1
References: 114

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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Genomics and Rare Diseases Machine Learning in Healthcare

Publication details

Journal / source
iScience
Publisher
Elsevier BV
Volume
29
Issue
6
Pages
115962–115962
Publication date
1 May 2026
Language
EN