Latest AI and machine learning research in critical care for healthcare professionals.
Lung transplantation remains the only definitive treatment for patients with end-stage respiratory failure; however, it is burdened by a substantial risk of post-operative mortality. Current risk stratification methods, such as the Lung Transplant Risk Index, offer limited predictive performance and interpretability. This study introduces a novel predictive model based on topological transformers ...
Intravenous (IV) fluids are cornerstone for management of acute kidney injury (AKI) after sepsis but can cause fluid overload. Restrictive fluid strategy may benefit some patients, however, identifying them is challenging. Novel causal machine learning (ML) techniques can estimate heterogenous treatments effects (HTE) of IV fluids among these patients. To develop and validate causal ML framework t...
Human loss-of-function (LoF) variants affecting both copies of a gene (“human knockouts”) provide a unique opportunity to directly study function and ...
The National Early Warning Score (NEWS) is a nationally recommended, clinically implemented system, used to prevent patient deterioration. While numer...
Respiratory disease outbreaks burden U.S. healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag 1-2...
Sepsis remains a major cause of preventable pediatric hospital deaths in developing countries, with progress hindered by the lack of effective risk id...
Left ventricular filling pressure (LVFP) is associated with heart failure symptoms, a key prognostic marker, and a therapeutic target, but is difficul...
Accurate risk stratification in heart failure (HF) is crucial to guide clinical decisions, optimise therapeutic strategies and inform resource allocat...
Diabetes mellitus (DM) is a major risk factor for acquiring infections. Metformin, the first-line treatment for type 2 DM, is associated with benefici...
Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is critical for guiding therapeutic decisions and improvi...
Sepsis-induced immunosuppression, characterized by lymphopenia, is associated with adverse outcomes. We aimed to identify distinct lymphocyte recovery...
To develop a predictive tool capable of early identification of the risk of acute respiratory failure within 48 hours of hospital admission in patient...
Lower respiratory tract infection (LRTI) is a leading cause of morbidity and mortality among children admitted to paediatric intensive care units (PIC...
Exposure to chemical irritants in laboratory and medical environments poses significant health risks to workers, particularly in relation to asthma-li...
Systematic reviews (SRs) are essential for evidence-based practice but remain labor-intensive, especially during abstract screening. This study evalua...
Carbapenem-resistant Gram-negative bacteria (CR-GNB) represent a major health challenge due to limited therapeutic options, increased morbidity, and e...
Recent advances in deep learning have enabled the integration of heterogeneous data modalities for clinical prediction, allowing models to exploit com...
Interpretable scoring system can contribute to bridge the gap between the timeliness and complexity of diagnosing Alzheimer’s disease (AD) and promote...
Surgery is inherently associated with complications, making early detection the cornerstone of timely intervention and improved outcomes. Artificial i...
Optimizing immunosuppressive therapy remains central to improving long-term outcomes after kidney transplantation. Both induction and maintenance ther...