Artificial intelligence in paediatrics: Current events and challenges.

Area of Science:

• Pediatric Medicine
• Artificial Intelligence
• Health Informatics

Background:

• Artificial intelligence (AI) is increasingly integrated into healthcare.
• The 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral, Polyprofessional) offers a framework for modern healthcare.
• Paediatric care faces unique challenges in diagnosis, treatment, and resource management.

Purpose of the Study:

• To examine the application of AI in paediatric care.
• To evaluate AI's role within the 7P medicine model.
• To highlight AI's impact on paediatric disease management and public health sustainability.

Main Methods:

• Review of current AI applications in paediatric settings.
• Analysis of AI's contribution to diagnosis, treatment, and prevention in children.
• Case study presentation of successful AI implementation in paediatric care.

Main Results:

• AI demonstrates diverse applications in paediatric diagnosis, treatment, and disease management.
• AI contributes to preventive strategies and efficient healthcare resource management.
• Successful case examples illustrate AI's positive impact on paediatric care delivery.

Conclusions:

• AI has significant potential to improve paediatric care.
• Adoption of AI supports the transition towards a 7P medicine model in paediatrics.
• AI integration can enhance the sustainability of public health systems through improved paediatric healthcare.