Digital Paediatrics: Responsible AI and Digital Technologies from Neonatal to Adolescent Health

Digital technologies including AI are transforming paediatric healthcare by enabling early detection, continuous monitoring, and personalised interventions across home, school, and clinical settings. Unique developmental, ethical, and contextual factors distinguish paediatric applications from adult-focussed digital health, including autonomy, assent, parental consent, and age-appropriate design. Ensuring safety, privacy, and equity while delivering clinically meaningful outcomes is essential for trustworthy adoption, especially in neonatal care, where patients are physiologically fragile, data are highly dynamic, decisions are time-critical, and technologies are deployed at the very beginning of life, directly affecting both neonates and their families.This Research Topic seeks to map the opportunities and challenges of Digital Paediatrics, advancing evidence-based, responsible, and developmentally appropriate use of AI and digital tools to improve child and adolescent health outcomes. We aim to surface methods, governance models, and design principles that safeguard young people while enabling innovation. Key questions include how to establish robust clinical validity and safety, ensure privacy-by-design with evolving consent/assent, reduce algorithmic bias across diverse paediatric populations, and integrate digital solutions into routine care and everyday life with particular attention to neonatal and early-life applications, where digital technologies may have lifelong impact and where methodological, ethical, and regulatory challenges are especially pronounced.This Research Topic invites articles that address, but are not limited to, the following themes:o Age-appropriate, human-centred design for children and adolescents (usability, accessibility, multilingual and neurodiversity-inclusive interfaces);o Ethics, privacy, and data governance in paediatric contexts (consent/assent, parental involvement, data minimization, safeguarding, online harms);o Algorithmic fairness and bias mitigation for paediatric AI (imbalanced datasets, developmental variability, subgroup performance reporting);o Explainability and transparency of AI for families, clinicians, and young users (communication of risk/uncertainty, shared decision-making);o Clinical validation, safety, and regulatory pathways for paediatric digital tools (risk classification, post-market surveillance, real-world evidence);o Digital monitoring and clinical decision support in neonatal care: development, validation, and integration of AI-enabled tools and connected devices for NICU and postnatal settings, with attention to safety, reliability, and workflow fit;o Ethical, usability, and family-centred frameworks for neonatal technologies: consent and data governance in parent–infant dyads, age- and fragility-appropriate design, caregiver engagement, and support for NICU-to-home transitions and remote follow-up;o Digital biomarkers and high-frequency data analytics in neonates (waveforms, imaging, multimodal monitoring, early prediction of morbidity, personalised neonatal medicine);o Validation of digital endpoints and surrogate markers in neonatal trials;o Digital phenotyping and biomarker development using wearables, mobile, and ambient sensors in home, school, and clinic environments;o Remote monitoring and telehealth for children and adolescents with chronic conditions (e.g., asthma, diabetes, epilepsy), mental health disorders, neurodevelopmental or rare diseases, or those at risk for any of these conditions;o Data quality, interoperability, and secure integration with electronic health records, registries, and school health records (standards, data linkage, FAIR principles);o Engagement strategies and behaviour change in youth (gamification, adherence, family-centred care, equity across the digital divide);o Sustainable and inclusive data infrastructures (privacy-preserving analytics, federated learning, multicentre datasets, longitudinal and transition-of-care considerations);o Handling faulty or uncertain AI outputs in paediatric care (risk management, escalation protocols, clinician oversight, accountability);o Context-sensitive deployment and evaluation frameworks (school-based screening, community settings, low-resource environments, global health).We welcome original research, methodology papers, implementation studies, policy and ethics analyses, reviews, practice guidelines, and all other article types accepted by Frontiers in Digital Health that advance safe, effective, and equitable Digital Paediatrics. Submissions addressing diverse populations, cross-cultural contexts, and participatory approaches with youth and families are particularly encouraged. Topic editors: Florian B. Pokorny, Mirja Quante, Gerhard Pichler, Bernhard Schwaberger Source: https://www.frontiersin.org/research-topics/77770/digital-paediatrics-responsible-ai-and-digital-technologies-from-neonatal-to-adolescent-health