Machine Learning and Artificial Intelligence in Pediatric Healthcare
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 991
Special Issue Editor
Interests: pediatrics; critical care medicine; ICU; health systems research; sepsis; ARDS; respiratory failure; septic shock; artificial intelligence; machine learning; ECMO
Special Issue Information
Dear Colleagues,
The integration of machine learning (ML) and artificial intelligence (AI) into pediatric healthcare represents a transformative shift in how we diagnose, prognosticate, and treat conditions in children. Pediatric patients present unique clinical challenges, including developmental variability, ethical considerations, and limited availability of diverse datasets. These challenges require innovative solutions that ML and AI are uniquely positioned to address, leveraging their ability to analyze complex patterns in vast datasets and deliver actionable insights.
This Special Issue, entitled "Machine Learning and Artificial Intelligence in Pediatric Healthcare", will showcase cutting-edge research and reviews that highlight the applications, methodologies, and challenges of ML and AI in advancing pediatric care. Contributions are invited that explore the development and validation of AI and ML-driven diagnostic tools, prognostic models for critical and chronic pediatric conditions, and AI-based strategies for personalized therapeutic planning. We also welcome submissions addressing the ethical, regulatory, and implementation challenges associated with ML and AI in pediatrics.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Diagnostic and prognostic models for pediatric diseases using AI/ML;
- Applications of explainable AI in pediatric clinical decision-making;
- Innovative ML techniques for small and imbalanced pediatric datasets;
- AI-enhanced imaging and wearable sensor applications in pediatric care;
- Ethical and regulatory frameworks for ML in pediatric healthcare;
- Real-world implementation and integration of AI/ML systems in pediatric clinical workflows;
- Advances in federated learning for secure and scalable pediatric healthcare applications;
- AI applications in improving outcomes for pediatric rare diseases and under-represented populations.
This Special Issue builds on the growing body of evidence showcasing how ML can improve diagnostic precision, reduce healthcare disparities, and optimize care delivery in pediatric populations. We anticipate that the insights and methodologies presented will help to shape the future of pediatric healthcare, ensuring equitable and effective AI-driven solutions for all children.
We look forward to receiving your contributions to this exciting and rapidly evolving field.
Dr. Hammad Ashraf Ganatra
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- pediatrics
- natural language processing
- diagnostics
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