aceDevelopment and validation of VentPilot: an AI-based recommendation system for mechanical ventilation
Background Mechanical ventilation requires repeated adjustment to changing patient physiology, but consistent individualized management remains challenging. We developed VentPilot, an artificial intelligence-based system for recommending ventilator settings, and evaluated it in multicenter retrospective validation cohorts. Methods VentPilot was developed using offline reinforcement learning on high-resolution physiologic and ventilator trajectories from Seoul National University Hospital (SNUH), with a reward co…
In multicenter retrospective validation, greater concordance between clinician ventilator settings and VentPilot AI recommendations was associated with more ventilator-free days within 28 days, lower 28-day mortality, and shorter ICU length of stay.
Findings are from retrospective validation cohorts only, with no prospective or interventional testing of safety, usability, or clinical impact.
Evidence
- Peer-reviewedJournal of Intensive Care2026-10-01
How should this claim be treated?
Truvace Impact Record TRV-2026-1243, v1: “Development and validation of VentPilot: an AI-based recommendation system for mechanical ventilation.” Truvace, 2026-10-02. /record/TRV-2026-1243 (accessed at citation time). sha256 9141868a380fbf8b…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1243 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.