Artificial intelligence and clinical decision support in paediatrics — viva

Opening (must-hit)

"Artificial intelligence in paediatrics is a computer system that performs a task a clinician would otherwise do by judgement. The four classes are prediction and early warning (the deterioration, sepsis and PICU-transfer score), diagnosis and image interpretation (the radiograph, retinopathy-of-prematurity and skull-fracture reader), rule-based decision support (the drug-interaction, dosing and allergy alert) and generative or triage tools. The candidate must distinguish a trained prediction model from a rule-based alert, because the two are validated and governed differently. The validation ladder is internal cross-validation, external validation in a different population, and a prospective silent trial — external validation is the gate. Sensitivity and specificity are not fixed but shift with prevalence and threshold, and the clinician remains accountable for every output. The four safeguards are clinician over-read, a written escalation plan, alert stewardship and ongoing monitoring." ^{[2] [10]}