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Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

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Transforming Pediatric Care Through AI: Bridging the Digital Divide in Health Informatics.

Mercy Mbogori-Kairichi¹, R Sterling Snead¹, Julia Marczika¹

¹Research Department, The Self Research Institute, 18452 E 111th St, Broken Arrow, OK, 74011, United States, 1 701155273.

Online Journal of Public Health Informatics

|May 13, 2026

Summary

This summary is machine-generated.

Artificial intelligence (AI) in health informatics can enhance pediatric care, improving diagnostics and treatment. Strategic development of interoperable systems and equitable infrastructure is crucial for widespread AI adoption in global child health.

Keywords:

artificial intelligence digital health electronic health records health informatics health information systems pediatrics

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Last Updated: May 15, 2026

Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

Bridging the Technology Divide in the COVID-19 Era: Using Virtual Outreach to Expose Middle and High School Students to Imaging Technology

Published on: September 28, 2022

Area of Science:

Health Informatics
Artificial Intelligence (AI)
Pediatric Health Care

Background:

AI and health informatics are transforming pediatric care delivery globally.
These technologies offer potential for improved diagnostics, personalized treatments, and wider access to care.
This viewpoint explores integrating health informatics frameworks with AI to address global pediatric care challenges.

Purpose of the Study:

To examine how health informatics and AI can overcome persistent challenges in global pediatric care.
To highlight the potential of AI-enabled clinical decision support in pediatric settings.
To discuss implementation barriers and propose strategic solutions for AI in pediatric health.

Main Methods:

Viewpoint paper based on selected studies and digital health guidance.
Analysis of evidence from clinical implementations of AI in pediatric care.
Case study review of AI applications in diverse pediatric settings.

Main Results:

AI embedded in electronic health records can improve pediatric diagnostic accuracy, e.g., diagnosing serious bacterial infections in infants.
AI-enabled clinical decision support shows diverse applications in neonatal intensive care and autism screening.
Implementation challenges include interoperability, data standardization, infrastructure gaps, and algorithmic bias.

Conclusions:

Strategic development of interoperable health information systems is essential.
Standardized data governance frameworks are critical for responsible AI implementation.
Equitable digital infrastructure is necessary to scale AI-enhanced pediatric care globally.