Latest AI and machine learning research in critical care for healthcare professionals.
BACKGROUND: Acute kidney injury (AKI) is a major complication in critically ill patients, burdening both patients and healthcare systems. We previously introduced an AI-based model for early and continuous prediction of ICU-acquired AKI (ICU-A-AKI-2/3). In this study, we enhanced the model to better handle missing data, a common challenge in clinical settings. The upgraded model was validated in b...
BACKGROUND: Sepsis patients face a high mortality risk. Available prognostic biomarkers have certain limitations. This study explored the prognostic utility of the PaO2/FiO2-to-PaCO2 ratio (PFP) in sepsis. METHODS: This study analyzed MIMIC-IV data on 16,546 patients with sepsis admitted to the ICU and categorized into three groups by PFP values calculated from the first arterial blood gas within ...
Smart rings enable unobtrusive monitoring of cardiovascular vital signs via photoplethysmography (PPG), yet rigorous validation is limited by the scar...
Histological analysis is a cornerstone of pre-clinical respiratory disease research. It enables assessment of pathology, therapeutic effects, and mech...
BACKGROUND: Hepatitis, a disease characterised by inflammation of the liver, is a leading global health challenge that contributes to over 1.3 million...
BACKGROUND: Spirometry remains the gold standard for assessing pulmonary function. Deep learning models have demonstrated potential for estimating mea...
Drug induced liver toxicity remains the most common cause of acute liver failure. Conventional toxicity detection relies on resource-intensive in vivo...
BACKGROUND: Early detection of sepsis in pediatric intensive care units (PICUs) is critical, but challenging due to its nonspecific clinical presentat...
OBJECTIVE: Acute kidney injury (AKI) is a severe complication following coronary artery bypass grafting(CABG) While machine learning models trained on...
BACKGROUND: Accurate preoperative risk stratification remains challenging, as existing scoring systems are often complex, invasive, or limited to spec...
Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving crit...
PURPOSE: While acute brain dysfunction (ABD, i.e., delirium and coma) is associated with significantly increased morbidity in critically ill patients,...
BACKGROUND: Rheumatoid arthritis patients in the ICU face a high risk of mortality. While traditional ICU scoring systems are not specifically designe...
CRISPR/Cas systems hold great promise for molecular diagnostics, but their amplification-free applications are hampered by weak signals and poor quant...
BACKGROUND: Elexacaftor-Tezacaftor-Ivacaftor (ETI) therapy markedly improves pulmonary function in people with cystic fibrosis (pwCF) but induces weig...
BACKGROUND: Sepsis-induced ARDS demonstrated greater severity and higher mortality compared to ARDS triggered by other factors. In this article, we co...
Artificial intelligence (AI) technologies such as machine learning (ML), deep learning (DL), predictive analytics and other tools are rapidly changing...
A common neurological symptom in dialysis patients is hemodialysis-related headache (HRH), which can result in premature hemodialysis termination and ...
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is increasingly recognized as a systemic inflammatory condition closely linked to metabolic d...
Prognostic assessment of diabetic kidney disease (DKD) is essential for personalized management. This study developed eight machine learning models us...