This observational study aims to determine whether an AI-assisted decision support system can improve clinical outcomes for mechanically ventilated pediatric patients (aged 1 month to 18 years) in the PICU, compared to standard care provided by medical staff. The primary question addressed is: Do patients whose ventilator parameter optimization decisions are guided by AI assistance achieve a greater number of ventilator-free days within 28 days than those managed by medical staff? By utilizing clinical data collected following tracheal intubation to generate AI-driven recommendations-and comparing these against the actual adjustments made by physicians-this study seeks to assess whether the AI-assisted decision support system can effectively improve clinical outcomes for mechanically ventilated patients in the PICU.

Inclusion Criteria:

1. PICU patients aged 1 month to 18 years.
2. Receiving invasive mechanical ventilation, expected to last ≥ 48 hours.
3. Informed consent signed prior to enrollment.

Exclusion Criteria:

1. Expected survival < 24 hours
2. Irreversible brain injury (GCS = 3 + absence of brainstem reflexes)
3. Severe congenital cardiopulmonary malformations affecting ventilation assessment
4. Pregnancy (must be ruled out in adolescent girls)
5. Currently participating in other ventilation intervention trials
6. Guardian refusal to participate

Pediatric patients aged 1 month to 18 years admitted to the Pediatric Intensive Care Unit (PICU) of the Second Affiliated Hospital of Wenzhou Medical University and Yuying Children's Hospital, who are receiving mechanical ventilation.

Individual participant data will not be shared, the study's ethical approvals and consent agreements do not permit public data sharing. Access may be considered upon reasonable request to the corresponding author, subject to institutional review and data use agreements to ensure patient privacy and compliance with regulations.