aceArtificial Intelligence Prognostic Models for Healthcare-Associated Infection Prediction in Adult Intensive Care Units: A Systematic Review Protocol
Background and aims Despite widespread Infection Prevention and Control (IPC) measures, Healthcare-Associated Infections (HAIs) remain a major concern in Intensive Care Units (ICUs), leading to increased mortality, prolonged hospital stays, and additional healthcare costs. Prognostic prediction models support identification of patients at high infection risk, and Machine Learning and Artificial Intelligence (ML/AI) methods offer the potential to improve such predictions. However, no systematic review has specifi…
Healthcare-associated infections persist in adult ICUs despite prevention measures, and no systematic review has yet examined the quality or readiness of ML/AI models meant to predict them.
As a protocol, it reports no results, so the reliability and clinical readiness of ML/AI infection prediction models in ICUs has not yet been established.
Evidence
- Peer-reviewedHealth Science Reports2026-10-05
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Truvace Impact Record TRV-2026-1846, v1: “Artificial Intelligence Prognostic Models for Healthcare-Associated Infection Prediction in Adult Intensive Care Units: A Systematic Review Protocol.” Truvace, 2026-10-18. /record/TRV-2026-1846 (accessed at citation time). sha256 6081d5df148787ff…
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