Summary: This article reviews AI applications for school nursing with an academic and public health orientation. It synthesizes vision/hearing screening automation, absenteeism analytics, and mental health triage support.
School nurses deliver preventive screening and early intervention for children. AI can automate screening interpretation, identify absenteeism patterns that signal outbreaks or social needs, and triage students for nurse follow up while safeguarding parental consent and child privacy.
Technically systems include image analysis for vision screening, audio processing for hearing checks, attendance pattern anomaly detection, and NLP for counselor notes. Validation requires pediatric school cohorts, parental consent processes, and measurement of outcomes such as referral rates and school attendance.
Guidance: For school health teams: obtain parental consent, validate tools in diverse pediatric populations, integrate with school health records, co?design communication templates for families, and ensure low?tech alternatives for equity.
Conclusion: AI in school nursing can expand screening capacity and population surveillance when validated for children, consented by families, and integrated with nurse workflows.
Final Summary: vision/hearing automation; absenteeism analytics; mental health triage; consent; equity
Useful Facts: school health | pediatrics | public health
Related Topics: nursing;school health Automated vision screening reduces referral burden; Attendance analytics detect outbreaks; Parental consent is mandatory; Pediatric validation across ages is required; Low?tech options ensure equity