Artificial Intelligence and the Management of Viral Respiratory Infections in Children
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Abstract
Viral respiratory infections in children are a major public health issue, with high incidence rates and a significant impact on healthcare systems. The application of artificial intelligence (AI) in the medical field offers substantial opportunities for early detection, accurate diagnosis, effective management, and prevention of these infections.
Aim: This study aims to analyse the most effective AI-based approaches for managing viral respiratory infections in children, including its application in paediatric hospitals, telemedicine, and routine practices, while also identifying challenges associated with implementation.
Methodology: A systematic literature review was conducted following the PRISMA guidelines. The search was performed across 10 major databases: De Gruyter, MDPI, Nature, PubMed, ScienceDirect, Elsevier, SpringerLink, Wiley Online Library, Taylor & Francis, and Frontiers, focusing on articles published between 2020 and 2024. Out of 46,900 scientific articles, 17 relevant studies were selected, including original research, meta-analyses, and systematic reviews.Results: AI has shown high efficiency in the early detection of symptoms, differential diagnosis between viral and bacterial infections, monitoring disease progression, and personalising treatments. Its use in telemedicine and family education has improved accessibility to care and raised awareness. Integration of AI in paediatric hospitals has reduced diagnostic time and optimised resources. However, large-scale implementation depends on collaboration between medical professionals and IT specialists.
Conclusions: AI represents a promising solution for improving the management of viral respiratory infections in children. The development of standardised protocols and addressing ethical challenges are essential for the effective integration of this technology into paediatric practice.
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