A retrospective records review comparing the care of patients who either avoided or were admitted to an ICU following a ward-based deterioration event
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Maternal early warning scores shown to be methodologically weak and at high risk of bias
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Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data.
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Explainability in the age of large language models for healthcare.
Mesinovic M. et al, (2025), Commun Eng, 4
Is age associated with different vital signs in adults presenting to hospital with bacterial infection? A systematic review and meta-analysis
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Oxygen therapy in early warning scores: a systematic review and meta-analysis
Harrison CH. et al, (2025), Thorax
Severe Maternal Morbidity in the High Income Setting: a Systematic Review of Composite Definitions
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Track-and-Trigger System: Identifying and Predicting Patient Deterioration through Scores and Algorithms
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Perioperative risk scores: prediction, pitfalls, and progress
Bedford JP. et al, (2024), Current Opinion in Anaesthesiology
Atrial fibrillation after cardiac surgery: identifying candidate predictors through a Delphi process
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Successfully initiating an escalation of care in acute ward settings—A qualitative observational study
Ede J. et al, (2024), Journal of Advanced Nursing
Effect of Digital Early Warning Scores on Hospital Vital Sign Observation Protocol Adherence: Stepped-Wedge Evaluation.
Wong DC-W. et al, (2024), J Med Internet Res, 26
Using a novel ambulatory monitoring system to support patient safety on an acute infectious disease ward during an unfolding pandemic
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Development of a national maternity early warning score: centile based score development and Delphi informed escalation pathways
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Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.
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Are Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare?
Gu X. et al, (2024), Proceedings of Machine Learning Research, 259, 401 - 419
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Luo Z. et al, (2024), Proceedings of Machine Learning Research, 235, 33432 - 33465
Improving escalation of deteriorating patients through cognitive task analysis: Understanding differences between work-as-prescribed and work-as-done.
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