Artificial Intelligence in Pediatric Imaging: Current Capabilities and Future Directions
A special issue of Children (ISSN 2227-9067). This special issue belongs to the section "Pediatric Radiology".
Deadline for manuscript submissions: 25 May 2026 | Viewed by 4
Special Issue Editor
Interests: artificial intelligence in pediatric neuroimaging; AI-driven prediction of neurocognitive outcomes; multimodal integration of MRI, genetics and clinical data, learning for brain development and neurodevelopmental disorder; radiogenomics for pediatric populations; machine learning for indi-vidualized neurocognitive risk assessment; AI methods for congenital heart disease–related brain and cognitive outcome; structural and functional MRI–based cognitive prediction; precision medicine through multimodal AI; predictive modeling of neurodevelopment using imaging and genomics; pediatric imaging informatics and computational neuroscience; translational AI for early detection of neurodevelopmental impairment
Special Issue Information
Dear Colleagues,
Artificial intelligence is rapidly reshaping pediatric imaging, building on advances in deep learning, radiomics, and automated volumetric tools to improve diagnosis, risk stratification, and longitudinal brain development assessment in children. The historical arc from handcrafted features to multimodal, data-driven radiogenomic models has created noninvasive links between imaging phenotypes and molecular or genetic signatures. This Special Issue aims to showcase translational AI that advances pediatric neuroimaging and oncologic imaging. It emphasizes explainability and promotes robust clinical validation and governance for child-specific tools. We welcome cutting-edge work on brain age and developmental–trajectory models, radiogenomics, multimodal MRI–genetic integration, foundation or transfer-learning approaches, and explainable AI methods with clinical evaluation. Original research, technical notes, large curated pediatric datasets, clinical validation studies, systematic reviews, and ethics/governance analyses are welcome.
Dr. Mohammad Arafat Hussain
Guest Editor
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Keywords
- pediatric imaging
- artificial intelligence
- deep learning
- radiomics and radiogenomics
- structural and functional mri
- neurodevelopment and brain maturation
- congenital heart disease (CHD) neuroimaging
- explainable and interpretable ai
- multimodal data integration
- clinical decision support in pediatrics
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